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4-year postdoc position in neural systems modelling at the University of Oslo
by Gaute Einevoll 09 Dec '17

09 Dec '17

Postdoctoral Research Fellowship in Neural Systems Modelling Position as postdoctoral research fellow available at the Department of Bioscience at the University of Oslo. The fellowship period is 4 years, with 25 % compulsory work. Anticipated start date is 01.02.2018. Project description: We study neural processing and plasticity of neural circuits at multiple levels, from the morphological changes at the synapse to functional changes of network activity in behaving animals. The position will be part of the project 'BrainMatrix' funded by the Norwegian Research Council, and seeks to explore the biophysical and physiological roles of perineuronal nets (PNNs) in neuron information processing and plasticity. PNNs are extracellular protein complexes thought to act as long-lasting synaptic anchors, thereby defining stable structural and functional connectivity in widespread but discrete regions of the brain. The entire BrainMatrix project is built on interdisciplinary principles and will involve strong interaction between mathematical modelling and experimental goals across the levels of investigation. As such, a key feature of this position will be to work between the outstanding computational and experimental groups at Simula Research Laboratory (www.simula.no)<http://www.simula.no%29/> andthe University of Oslo (www.mn.uio.no/ibv/english/research/sections/fyscell/cinpla)<http://www.mn.uio.no/ibv/english/research/sections/fyscell/cinpla)>. For this reason, the candidate should have experience in either computational neurophysiology/cell electrophysiology or experimental, and a strong desire and potential to expand their skillset to include the other discipline. Job description: We are searching to fill a 4-year full time postdoctoral, with 75% of the time devoted to research and 25% reserved for other career promoting activities such as lecturing or mentoring. The successful candidate will develop and implement models for interrogating the effects of genetic and pharmacologic manipulation of PNNs on single neuron and network function in visual and spatial information processing. The modeling approach will take advantage of tools and resources available through the Human Brain Project, and developed locally such as the NEST and LFPy simulators. The experimental goals will involve opportunities to apply or learn classical slice electrophysiology and single/multi-unit extracellular recordings, as well as advanced in vivo optical recordings and in vivo patch clamping. Within the framework of the position duties corresponding to one year of compulsory work may be assigned. For more information, including on how to apply, see: https://www.jobbnorge.no/ledige-stillinger/stilling/145487/postdoctoral-res… Deadline for application: January 10th 2018 For questions, please contact: Associate Professor Andy Edwards, phone: +47 40472451, e-mail:andrew.edwards@ibv.uio.no ********************************************** Gaute T. Einevoll Faculty of Science and Technology Norwegian University of Life Sciences, 1432 Aas, Norway; Department of Physics, University of Oslo, Oslo, Norway Ph. +47-64965433, Mobile: +47-95124536 email: Gaute.Einevoll(a)nmbu.no<mailto:Gaute.Einevoll@nmbu.no>, web: compneuro.nmbu.no, cinpla.org

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PhD positions at the University of Bristol
by Tsaneva-Atanasova, Krasimira 08 Dec '17

08 Dec '17

Wellcome Trust 4 year PhD Programme in Neural Dynamics University of Bristol Deadline for applications: Sunday 7 January 2018 Why investigate neural dynamics? A vital key to comprehending the brain is to understand how the complex changes in activity occurring at all levels of neural organization give rise to normal brain function. Furthermore, an understanding of normal brain activity will allow us to investigate abnormalities of neural dynamics that underlie many neurological and psychiatric disorders (e.g. epilepsy, Parkinson’s disease, schizophrenia). Understanding neural dynamics<https://www.findaphd.com/common/clickCount.aspx?theid=602&type=185&url=http…> requires interdisciplinary approaches that span many neuroscience areas, but crucially, also depends on the integration of experimental and clinical approaches with mathematical and computational expertise. This PhD programme trains a future generation of neuroscientists to successfully combine experimental and theoretical techniques in their research. Structure of the programme First year: students attend taught courses to gain an understanding of the biology of the nervous system and the ability to describe systems dynamics in mathematical models. Students carry out two extended research projects, each investigating dynamics in a different neural system. Each project is co-advised by one experimental or clinical neuroscientist and one mathematician or computer scientist. Subsequent years: Students develop one of the initial projects into a PhD project for the remaining 3 years. Who are we looking for? Applicants will have a 1st class/2.1 degree or a Masters in a biomedical science discipline or a relevant theoretical discipline (mathematics, computer science or physics). Crucially, we are looking for talented and motivated students willing to take up the many challenges in neural dynamics and who are open to learning about new disciplines and working across different fields. Why study at Bristol? Bristol has one of the largest concentrations of neuroscientists in Europe and is a major centre for basic and clinical neuroscience. The University of Bristol is an acknowledged world leader in many key areas of neural dynamics from both an experimental and theoretical perspective: Our research spans molecular, cellular and systems levels of neuroscience. Together with experts in systems dynamics, based in the Departments of Engineering Mathematics, Mathematics, Computer Science and the Bristol Robotics Lab we can provide considerable scope for ground breaking integrative research projects. How to apply: Application process: Please apply online at www.bris.ac.uk/study/postgraduate/apply<https://www.findaphd.com/common/clickCount.aspx?theid=602&type=185&url=http…> by selecting ‘Faculty of Biomedical Sciences’ and ‘Wellcome 4-year PhD in Neural Dynamics’ Please ensure you include a CV, and two referees plus a cover letter outlining your own neuroscience interests by Sunday 7 January 2018. Please upload your covering letter into the Personal Statement section of the application form. Shortlisted applicants will be invited to an interview in late January. The Wellcome Trust provides a stipend and PhD registration fees at UK/EU student rate, research expenses, contribution towards travel and a contribution towards transferable-skills training. The Wellcome Trust does not pay fees at the overseas rate. For further information please see www.bristol.ac.uk/neural-dynamics<https://www.findaphd.com/common/clickCount.aspx?theid=602&type=185&url=http…> or contact: Lindsey Watson, Graduate Administration Manager, Faculty of Biomedical Sciences, Graduate School (Lindsey.Watson(a)bris.ac.uk)

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Scientist opening at the Allen Institute: "Simulation & Analysis of Human Circuit Dynamics"
by Costas Anastassiou 07 Dec '17

07 Dec '17

Dear All: We are seeking a Scientist to be an essential team member in our ongoing effort to understand how the human brain processes information. The core responsibility for this position is to setup large-scale computational simulations and data analysis workflows from slice and in vivo brain physiology in humans. Find the full job description attached below. To apply for this position, apply through the link below: https://apply.hrmdirect.com/resumedirect/ApplyOnline/Apply.aspx?req_id=6535… Best, Costas -- Costas Anastassiou Assistant Investigator T: 206.548.8434 E: costasa(a)alleninstitute.org alleninstitute.org Professor (adj.) of Neurology University of British Columbia, Vancouver BC, CA http://neuroscience.ubc.ca/people/Anastassiou Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. By implementing a team science approach on a large scale, we strive to generate useful public resources, drive technological innovations and discover fundamental brain properties through integration of experiments, modeling and theory. POSITION SUMMARY We are seeking a Scientist to be an essential team member in our ongoing effort to understand how the human brain processes information. The core responsibility for this position is to setup large-scale computational simulations and data analysis workflows from slice and in vivo brain physiology in humans. More specifically, the Scientist will (i) design and conduct simulations with an existing large-scale computational framework allowing simulation of a multitude of reconstructed, interconnected and biophysically realistic human neurons (e.g. [Schomburg, Anastassiou et al, J Neurosci, 2012; Reimann, Anastassiou et al, Neuron, 2013]; (ii) analyze simulated and experimental data to establish structure-function relationships (e.g. [Taxidis, Anastassiou et al, Neuron, 2015]); (iii) develop dimensionally reduced representations of neural function (e.g. using machine learning or statistical data modeling) based on recorded signals (encoding) and develop methods for reconstructing! neural function from neural activity (decoding); (iv) compare computational findings with experimental observables. ESSENTIAL DUTIES AND RESPONSIBILITIES In close collaboration with theoreticians and experimental colleagues, design, implement and conduct single-neuron and large-scale network simulations of human middle temporal gyrus. Contribute to ongoing efforts in computational framework development (simulation and data analysis) as well as to scientific questions relevant to the system under investigation. Contribute to adjacent projects related to human pathophysiology and neurotherapies. Publish/present findings in peer-reviewed journals/scientific conferences. Prepare written and oral reports on a regular basis. Maintain clear and accurate communication with supervisor, team members and external collaborators. BASIC QUALIFICATIONS PhD degree in computational neuroscience, physics, applied mathematics, bioengineering or related field. Strong background in scientific computing; experience in computational neuroscience is preferred, but other strong applicants will be considered (with background in computational physics, applied mathematics, biophysics, and related disciplines). Experience with parallel computing is a plus as well as familiarity with high-level programming languages such as Python. Familiarity with in vitro and in vivo electrophysiological monitoring techniques and analysis. DESIRED QUALIFICATIONS: Ability to meet aggressive timelines and deliverables in a collaborative environment. Strong publication record. Experience in pursuing research projects in collaborative fashion. Proven independent thinking and flexibility. Strong written and verbal communication skills.

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[SUSPECTED SPAM] PhD at Florida Atlantic Universitys Center for Complex Systems and Brain Sciences
by Emmanuelle Tognoli 07 Dec '17

07 Dec '17

Applications are currently being accepted for fully funded multidisciplinary PhD training in Complex Systems & Brain Sciences (http://www.ccs.fau.edu/phd_overview.php) at Florida Atlantic University. Students will be trained to perform cutting-edge brain research that combines neuro-behavioral and cognitive experiments, laboratory neurobiology, medical imaging, and computational/theoretical modeling. Research projects will focus on approaches to understanding the brain as a complex dynamical system, with possible concentrations in areas such as cognitive, developmental, social, and systems neuroscience, neurorobotics, molecular and cellular neurobiology, and neuronal regeneration. Individuals with undergraduate degrees in any pertinent discipline are invited to apply. Two routes are available to enter the PhD program: the Graduate Neuroscience Training Program (http://www.ibrain.fau.edu/gradneuro/) or directly into the core program from the Center for Complex Systems & Brain Sciences (http://www.ccs.fau.edu/requirements.php) Applicants should review both tracks to determine which one best suits their interests. Students may also submit applications to both tracks. Application deadline for the Graduate Neuroscience Training Program: December 11, 2017 Application deadline for the core PhD program in Complex Systems & Brain Sciences: January 15, 2018 -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean. -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean.

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Fully-funded four-year PhD studentship in Computational Neuroscience at Imperial College London
by Reichenbach, Johann D T 06 Dec '17

06 Dec '17

An exciting PhD project in Computational Multisensory Neuroscience is available for UK/EU candidates in the group of Tobias Reichenbach (http://www.bg.ic.ac.uk/research/reichenbach/index.html) at Imperial College London. The student will develop state-of-the art neuronal network models to investigate the effects of custom-build tactile stimuli on speech processing. The model development and results will be linked with neuroimaging and behavioural experiments, and will pave the way to aid speech comprehension in people with hearing impairments. The PhD position is part of the Center for Neurotechnology (http://www.imperial.ac.uk/neurotechnology/cdt) at Imperial College London. The successful candidate will join an international cohort of PhD students working on cutting-edge topics of computational and experimental neuroscience and engineering. To apply please visit the Centre's project page (http://www.imperial.ac.uk/neurotechnology/cdt/projects/) access the tab "Projects available for Oct 2018" and select the project "Engineering tactile signals to aid hearing in noisy backgrounds.” ------------------------------------------- Tobias Reichenbach Senior Lecturer (Associate Professor) Department of Bioengineering Imperial College London South Kensington Campus SW7 2AZ London, UK http://www.bg.ic.ac.uk/research/reichenbach/

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PhD or postdoctoral position at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany
by Filip Sobczak 05 Dec '17

05 Dec '17

Dear Colleagues, The Department of High-field Magnetic Resonance at the Max Plank Institute for Biological Cybernetics in Tübingen is offering one PhD or postdoctoral position under the supervision of Dr. Xin Yu (Group Leader at MPI for Biological Cybernetics). This position is open now until filled, starting in Jan, 2018. Research Description: Understand and learn to control the brain circuits underlying critical brain states, such as coma or arousal. Potential assignment: a) Build up a real-time bio-feedback controlling system for brain functional studies: i) Neural network system-based signal processing, ii) MR-guided robotic system development, iii) Machine learning-based multi-modal brain signal dynamic prediction. b) Implement the MRI/EEG/calcium recording methods for global brain state monitoring. c) Target specific nuclei with deep brain optogenetic stimulation methods to study circuit-specific brain state neuromodulation: hippocampus, lateral hypothalamus, and VTA. Students with strong computational skills are highly encouraged to apply for this position. Experience with viral transfection, or in vivo. / in vitro. electrophysiology in animal models (rodents) with brain injury is highly desirable. The candidates should bear a certain experience or strong interest in brain functional imaging, e.g. task-based BOLD fMRI. The Max Plank Institute for Biological Cybernetics is located in Tübingen, Germany. The High-field Magnetic Resonance Department is equipped with the 3T, 9.4T human MR scanner and 14.1T animal Bruker MR Scanner. The Max Planck Society is an affirmative action/equal opportunity employer, and encourages applications from qualified women and minority candidates. Please send your CV (in English) to Dr. Yu (E-mail: xin.yu(a)tuebingen.mpg.de ). Dr. Yu has published seminal papers on high field MRI functional brain mapping in Nature Neuroscience, Nature Methods, Neuron, PNAS, NeuroImage etc.

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Postdoctoral Associate Positions in Computational Psychiatry, Virginia Tech Carilion Research Institute
by Pearl Chiu 04 Dec '17

04 Dec '17

Postdoctoral Associate Positions in Computational Psychiatry Virginia Tech Carilion Research Institute Multiple postdoctoral associate positions are available immediately in the labs of Dr. Pearl Chiu and Dr. Brooks King-Casas at the Virginia Tech Carilion Research Institute (http://research.vtc.vt.edu/) Projects in the labs use fMRI to examine the neuroscience of motivated behavior and social influences on decision-making with methods from behavioral & computational neuroscience, experimental economics, computational psychiatry, and psychology; ongoing projects examine processes in healthy and psychiatric individuals. Qualified candidates with basic science, theoretical, and/or computational backgrounds are welcome, and training in applied science will be provided; a subset of projects also involve multi-dimensional biomarker development. For interested candidates, the labs provide plentiful opportunities to examine how neurobehavioral anomalies may be quantified and rehabilitated in depression, substance dependence, post-traumatic stress, personality disorders, and at-risk adolescents. The labs are located in the Virginia Tech Carilion Research Institute in Roanoke, VA, just off the Blue Ridge Parkway. The VTCRI provides full access to outstanding infrastructure, including three research-dedicated Siemens 3T scanners and a high-throughput computing cluster. The successful candidate will play a lead role in highly collaborative multidisciplinary scientific efforts. Minimum requirements for the position include: 1) a PhD in computational or cognitive neuroscience, engineering, psychology, experimental economics, or a related field; 2) facility with computational neuroscience, signal processing, Bayesian inference, or machine learning; and 3) demonstrated potential for excellence. Please forward a statement of interest and CV. Three letters of recommendation will be requested from candidates under final consideration. Consideration of applications will begin immediately and will end when the positions are filled. Salary is competitive and will be commensurate with experience and qualifications. Virginia Tech Carilion is an Affirmative Action/Equal Opportunity employer and is committed to cultural diversity and compliance with the Americans with Disabilities Act. Send inquiries and materials to: Pearl Chiu, PhD and Brooks King-Casas, PhD chiup(a)vtc.vt.edu<mailto:chiup@vtc.vt.edu> and bkcasas(a)vtc.vt.edu<mailto:bkcasas@vtc.vt.edu>

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1 PhD/PostDoc position in neuromorphic systems
by elisabetta chicca 04 Dec '17

04 Dec '17

Dear colleagues, 1 PhD/PostDoc position is available at the Neuromorphic Behaving Systems group (https://www.cit-ec.de/en/nbs) Faculty of Technology and Center of Excellence Cognitive Interaction Technology at Bielefeld University. You can find details here: http://uni-bielefeld.de/Universitaet/Aktuelles/Stellenausschreibungen/Anzei… Best regards, Elisabetta Chicca -- Prof. Dr. Elisabetta Chicca CITEC - Bielefeld University Inspiration 1 33619 Bielefeld - Germany Tel.: +49 521 106-12043 Fax : +49 521 106-12348

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Master 2 internship
by Bruno Cessac 04 Dec '17

04 Dec '17

Decoding cortical activity evoked by artificial retinal implants The NeOpTo team (Institut des Neurosciences de la Timone, Marseille, France) and the Biovision Team (Inria, Sophia Antipolis, France) propose a joint Master 2 internship, entitled "Decoding cortical activity evoked by artificial retinal implants" from March 2018 to August 2018. The details of the internship can be found here https://team.inria.fr/biovision/files/2017/11/StageINT.pdf To apply, please send us a CV, a letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project, a transcript(s) giving full details of subjects studied and grades/marks obtained. Dr Bruno Cessac, Research Director at INRIA, Head of the BioVision team -INRIA 2004 Route des Lucioles-BP93 FR-06902 Sophia Antipolis Cedex

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira 02 Dec '17

02 Dec '17

Mathematical Modelling of Event-Related Potentials in Semantic Representation and Memory - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2891 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Professor Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298> Location Streatham Campus, Exeter Project Description N400 is an event-related potential (ERP) component that tap into semantic representation and memory and is an important markers of cognitive function, hence valuable clinical tools for quantifying integrity of the semantic system in populations with semantic comprehension deficit including stroke survivors, patients with traumatic brain injuries (TBI) or focal seizure disorders. Yet the neural origin of this component is largely unknown, which limits robustness of its measurement and clinical applicability. This project investigates the origin of N400, i.e., whether it emerges as a result of phase alignment in the ongoing oscillatory activity or as a result of an evoked neural activity. In the first stage of the project, the student will explore the neural dynamics of N400 by applying model-based data analysis and feature extraction to already collected in the second supervisor’s lab in Bristol human scalp electroencephalogram (EEG) data from healthy younger and older people responding to meaningful stimuli such as words, sentences or pictures of objects. This analysis will inform data-driven generative model(s) parameterization. In the second stage, the network models developed in stage 1 will be perturbed to identify the parameters (features) for conditions such as stroke and traumatic brain injuries (TBI). The final stage of the project will aim to link the event-related response with the underlying induced and evoked activity and to further investigate this activity using learning in the model space approach. There is a potential to reveal therapeutic targets for stroke and TBI. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in applied mathematics, computer science, physics or engineering. Experience in biomedical engineering or experimental psychology is desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira 02 Dec '17

02 Dec '17

Developing Gaze Training for Skilled Upper-Limb Prosthetic Use - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2892 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Professor Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298> Dr Gavin Buckingham<http://sshs.exeter.ac.uk/staff/index.php?web_id=Gavin_Buckingham> Dr Sam Vine<http://sshs.exeter.ac.uk/staff/index.php?web_id=Samuel_Vine> Professor Mark Wilson<http://sshs.exeter.ac.uk/staff/index.php?web_id=Mark_Wilson> Location Streatham Campus, Exeter Project Description Learning to use a prosthetic limb is inherently difficult and requires a huge amount of concentration. Like learning how to wield a new tool for the first time, amputees need to acquire the confidence and dexterity required for skilled action. In order to produce accurate goal-directed movements the motor system requires accurate and timely visual information making the timing and location of the person’s gaze, with relation to the movement of their limbs, critical for skilled behaviour. There is, however, no structured training protocol for use with prosthetic hands. We aim to develop a novel gaze training regime to facilitate the use of a prosthetic hand to skilfully interact with objects. In the first phase of the project, the student will undertake an observational study to determine what factors lead some individuals to become skilled with a prosthesis faster than others. We will test large numbers of intact (i.e., without amputation) participants learning to use a state-of-the-art myoelectric prosthetic arm simulator, which is controlled by muscle feedback but ergonomically designed to fit over the wrist of an intact hand. Participants will move objects of different of sizes and weights from one location to another with a range of precision requirements and in the presence of a range of obstacles. Over multiple sessions we will measure hand and object kinematics, fingertip forces, and eye path with a head-mounted eye tracker. We will then develop a data-driven mathematical model of the eye tracking and biomechanical performance data. Statistical analysis of the patterns of eye movement will provide new insights into the ‘signature’ of good performance using the prosthetic arm. The second phase will use the data from Project 1 to develop a training protocol that will adopt the ‘expert signatures’ from Phase 1 as a prototype for a trainee to follow. We will focus predominantly on the signature of expertise derived from the gaze behaviour measures and implement a gaze training protocol. We will then test the efficacy of this novel training regime with new set of intact participants using the prosthetic simulator, tracking their performance in comparison to individuals who will receive a sham training protocol. In the final phase of the project, the gaze training protocol will be used in a sample of upper-limb-amputees as they learn how to use their new prosthesis. As this stage of the project will not be limited to myoelectric prosthetic users, this will also allow us to test the generalizability of our training protocol. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in applied mathematics, computer science, physics or engineering. Experience in biomedical engineering or robotics is desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira 02 Dec '17

02 Dec '17

Understanding Emergent Complex Noisy Patterns in Biological Cells - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2890 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Associate Professor Jan Sieber<http://emps.exeter.ac.uk/mathematics/staff/js543> Prof Krasimira Tsaneva-Atanasova<https://emps.exeter.ac.uk/mathematics/staff/kt298> Dr Joel Tabak<http://medicine.exeter.ac.uk/people/profile/index.php?web_id=Joel_Tabak-Szn…> Location Streatham Campus, Exeter Project Description One of the most fascinating phenomena in nature is that small random disturbances can create systematic large-scale patterns of motion. Mathematically, this is described by the theory of nonlinear dynamics. One essential process governed by this theory is electrical signalling in animal and plant cells. Biological cells communicate with periodic or more complex patterns of electrical signals that underlie thinking, hormone release or muscle movement. These patterns are extremely sensitive to various types of noise present in cells such as rapid fluctuations and slow random drift. A general mathematical question is how precisely the different types of small noise perturbations influence the emergent patterns in nonlinear systems. Applications of the insights gained from mathematical analysis to understanding and controlling living cells would allow us to inform novel therapies for hormonal or neural disorders such as chronic stress response or essential tremor for example. Traditionally, mathematical modelling of cells has been applied to idealised, noise-free models. This funded PhD studentship will investigate how small noise drives and controls periodic and non-periodic patterns in general, and specifically in excitable cell models and experiments. The student will design a method to remove noise from emergent electrical patterns, using techniques from dynamical systems theory and feedback control theory. Joel Tabak (one of the project supervisors) has developed a proof of concept methodology for periodic patterns that is similar to what is used in noise-cancelling headphones, but uses concepts from dynamical systems to determine the perturbing noise. Being able to remove noise will allow us to compare the patterns in noisy and noise-free conditions. This will help scientists understanding how noise controls electrical patterns in many types of electrically active cells. The student will design further new methods for removing noise in mathematical models (ordinary differential equations) of electrically active cells. The PhD studentship will benefit from close collaboration with Joel Tabak’s neuroscience laboratory. This laboratory is able to perform experiments with live cells in real time using electrical signals in dynamic clamp experiments. Thus, the student will have the opportunity to immediately test how their methods perform in a real biological system, and use the experimental results as a guide to refine their methodology. By interacting with experimental researchers, the student will also gain important experience in working within a multidisciplinary scientific team. Depending on the student’s interests and progress during the PhD studentship, there will also be the opportunity to learn electrophysiology in order to record the electrical activity from live cells. This project would suit a student keen to 1) learn and apply new maths concepts (nonlinear dynamical systems, multi-scale analysis, stochastic processes); 2) interact with people from different scientific fields; and 3) present their results at national and international conferences. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in mathematics or a natural sciences or engineering programme with a strong quantitative component. Experience in nonlinear dynamics, mathematical biology or probability, and some programming experience are desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298 ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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NeuroMorpho.Org v7.3 released November 28th, 2017
by NeuroMorpho Administrator 02 Dec '17

02 Dec '17

Dear colleagues, We’re pleased to announce the November 28, 2017 release of Version 7.3 of NeuroMorpho.Org<http://neuromorpho.org/>, adding 9987 reconstructions from 96 new datasets. The repository now provides access to 80,012 cells and passed 8 million downloads in 166 countries. Please visit the What’s new page<http://neuromorpho.org/WIN.jsp> for details on the added data and metadata. The literature coverage was also updated to include publications through October 2017, with more than 1000 articles referencing data in this resource. We are continuously grateful to all data contributors<http://neuromorpho.org/acknowl.jsp#DC> who freely share their hard-won tracings with the community. We appreciate any and all feedback and comments. Our apologies if you receive multiple versions of this message through cross-listing. Sincerely, The NeuroMorpho.Org team<http://neuromorpho.org/acknowl.jsp#NMO> ---------------- Giorgio Ascoli<http://krasnow1.gmu.edu/cn3/ascoli>, PhD University Professor Bioengineering Department<http://bioengineering.gmu.edu/>, Volgenau School of Engineering<http://volgenau.gmu.edu/> Neuroscience Program<http://neuroscience.gmu.edu/>, Krasnow Institute for Advanced Study<http://krasnow1.gmu.edu/> Director, Center for Neural Informatics, Structures, & Plasticity<http://krasnow1.gmu.edu/cn3> MS2A1 - George Mason University<http://gmu.edu/>, Fairfax, VA 22030-4444 Ph. +1(703)993-4383/+1(703)673-8894 Author of “Trees of the Brain, Roots of the Mind<http://www.amazon.com/Trees-Brain-Roots-Giorgio-Ascoli/dp/0262028980/>” (MIT Press, 2015<http://mitpress.mit.edu/books/trees-brain-roots-mind>) Founding Editor-in-Chief, Neuroinformatics<http://link.springer.com/journal/12021>

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BECNC 2018 Conference
by Narges Chinichian 02 Dec '17

02 Dec '17

[Apologies for cross posting] Dear All I'm glad to announce that the "Brain Engineering & Computational Neuroscience Conference BECNC 2018" will be held on Jan 31 to Feb 2 in Tehran, Iran. Here is the link to register: https://becnc.ir/?page_id=452 <https://becnc.ir/?page_id=452> Keynote Speakers: Prof. Tipu Aziz (Oxford Univ., UK) Prof. Kenneth Miller (Columbia Univ., USA) Prof. Reza Shadmehr (JHU, USA) Prof. Pieter Roelfsema (NIN, Netherlands) Prof. Alexandre Pouget (Univ of Geneva) Prof. Susana Martinez-Conde (SUNY, USA) Prof. Susan J. Sara (College de France) Prof. Winrich Freiwald (Rockefeller Univ, USA) Prof. Gregor Rainer (Univ. of Fribourg, Switzerland) Prof. James Bisley (UCLA, USA) Prof. Qasim Zaidi (SUNY, USA) Prof. Yasser Roudi (NTNU, Norway) Prof. Valentin Dragoi (UT, USA) Prof. Frank Scharnowski (Univ. of Zürich, Switzerland) Prof. Alexander Thiele (Newcastle Univ., UK) Dr. Kamran Diba (Univ. of Michigan, USA) Dr. Ali Borji (UCF, USA) Dr. Qolamreza (Ray) Razlighi (Columbia Univ., USA) Dr. Morteza M. Goudarzi (MIT, USA) Dr. Koorosh Mirpour (UCLA, USA) Dr. Athena Akrami (Princeton Univ., USA) Dr. Yousef Salimpour (JHU, USA) Dr. Abbas Khani (Univ. of Geneva, Switzerland) see the complete list here: <http://goog_1578179254/> https://becnc.ir/?page_id=91 Dates & Deadlines: Abstract and full paper submission opening: November 4, 2017 Abstract submission deadline: January 10, 2018 Full paper submission deadline: January 11, 2018 Conference registration deadline: January 23, 2018 Late conference registration deadline (limited number): January 30, 2018 Main event: January 31 – February 2, 2018 There are also a workshop and a one-day course at the same time which you may like to attend. Find the details here: https://becnc.ir/?page_id=488 For more information, visit: https://becnc.ir/ Regards

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Data Engineer at Columbia University's Zuckerman Mind Brain Behavior Institute
by Rajendra Bose 01 Dec '17

01 Dec '17

Columbia University's Mortimer B. Zuckerman Mind Brain Behavior Institute (Zuckerman Institute) is seeking a highly motivated individual with strong software engineering skills, some familiarity with machine learning, and an interest in neuroscience and teaching to facilitate data analysis and sharing across 10 laboratories <https://zuckermaninstitute.columbia.edu/columbia-s-zuckerman-institute-awar…> investigating the computational and circuit mechanisms underlying motor control. For more information and to apply, see: https://zuckermaninstitute.columbia.edu/data-engineer Thank you— Raj Rajendra Bose, Ph.D. Director, Research Computing Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University Tel: 212-851-2918 http://zuckermaninstitute.columbia.edu

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Real World Eye Tracking course 2018 - booking now open
by Durant, Szonya 27 Nov '17

27 Nov '17

We are pleased to announce that booking for the Real World Eye Tracking Course April 16 +17, 2018 at Royal Holloway, University of London, is now open. This course is supported by the BBSRC and is accredited by the Market Research Society (counting for 12h Continued Professional Development). It is run jointly by the Dept. of Psychology, Royal Holloway and Acuity Intelligence Ltd. Why do you need to know about eye tracking? >From glasses you can use almost anywhere to laptops with them built-in and now augmented and virtual reality headsets - eye tracking is everywhere! But not all eye trackers are created equal, and to get the best out of this technology you need look around. Whether for simply knowing where a person looks or understanding cognitive states in high pressure environments, this is a technology you can't afford to ignore. Why we run this course We believe you need some theoretical background to get the most out of eye-tracking, but we also recognise the value that comes from the hands-on experience of designing, running and analysing real studies. Our aim is to give you the confidence to dive in and save you from drowning when you do! No other course offers this range of cutting edge multi-platform systems in one place, without a sales-person in sight! Try things out, and see the results for yourself. What you will learn How to justify your use of eye tracking methods and understand the evidence they provide Where to find further information when running your own projects How to choose the right tools and begin running your own project How to get the most out of your research through good design and great analysis Course content The course contains a mix of interactive lectures and small team project work supervised by an expert in the field. All attendees will experience running an eye tracking project from start to finish. You will also get to chat with experts and develop a feel for issues, independent of hardware and software platforms, from various research applications. Please see further details on https://www.royalholloway.ac.uk/psychology/research/eyetracking.aspx or book directly on https://www.eventbrite.com/e/real-world-eye-tracking-course-tickets-3969635… Please note, places often sell out quickly! We look forward to welcoming you in April! Best wishes Szonya Durant (RHUL) Tim Holmes (AI Ltd) ********************************************************************** Szonya Durant Department of Psychology Royal Holloway, University of London Egham TW20 0EX 01784 276522

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Postdoctoral Researcher at MPI Leipzig
by Thomas Knoesche 27 Nov '17

27 Nov '17

Dear colleagues, the Max-Planck-Institute for Human Cognitive and Brain Sciences (MPI-CBS, Leipzig, Germany) in seeking a Postdoctoral Researcher for a period of 3 years. The position is part of a collaboration between the Pompeu Fabra University at Barcelona, (G. Deco) and the MPI-CBS (A.D. Friederici, A. Anwander, T.R. Knösche), entitled "The Dynamic Connectome Underlying Language in the Brain" financed by the DFG priority program “Computational Connectomics”. You will work in a multidisciplinary team of computational and cognitive neuroscientists, imaging experts, biomedical engineers, neurologists, etc. The MPI-CBS offers excellent research facilities and prime imaging equipment (including 7T and CONNECTOM scanners). Project Description The neural language network is well described by systematic neuroscientific studies and may serve as an example for large scale cognitive networks within the human connectome. Important parameters of dynamic network models concern the structural/effective connectivity between brain areas. These connections are realized by bundles of axons with variable density, myelination status, and diameters. This results in complex transfer behavior, which is likely to have a profound influence onto the dynamics of the entire network. We plan to (i) establish a mathematical model for the transfer function between brain areas through fiber bundles, (ii) parameterize this model with individually measured white matter microstructure (acquired partly using novel high-gradient MR technology – CONNECTOM) and general data from the literature, (iii) incorporate this model into a dynamic network model (iv) explore the effect of the parameters onto the dynamics of canonical network architectures, (v) validate the model with electrophysiological calibration experiments, and (vi) use it to establish relations between language function and microstructural properties of brain tissue. The successful applicant should have a strong background in Computational Neuroscience, preferably including a PhD thesis in that area. Experience with modeling dynamic systems in neuroscience is necessary. A fair degree of neurobiological and neuroimaging understanding will be an advantage. Remuneration is based on the payscale of the Max Planck Society. The Max Planck society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Please submit your application via our online system at http://www.cbs.mpg.de/vacancies (using subject heading “PD 24/17”). Closing date for applications is December 15th, 2017. Contact for informal enquiries regarding the post: PD Dr.habil. Thomas R. Knösche (knoesche(a)cbs.mpg.de) For more information about the group see: http://www.cbs.mpg.de/methods-and-development-groups/meg-and-cortical-netwo… -- --- PD Dr.habil. Thomas R. Knösche Group Leader Research group "Cortical Networks and Cognitive Functions" Max Planck Institute for Human Cognitive and Brain Sciences Stephanstraße 1A, 04103 Leipzig, Germany Phone: +49 341 9940-2619 Fax: +49 341 9940 2624 Email: knoesche(a)cbs.mpg.de http://www.cbs.mpg.de/~knoesche

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[WCCI 2018 Special Session] Interpretable Deep Learning Classifiers
by Teng Teck Hou 23 Nov '17

23 Nov '17

[Apologies for cross-postings] Special Session on Interpretable Deep Learning Classifiers IEEE World Congress on Computational Intelligence 8 - 13 July 2018, Rio de Janeiro, Brazil www.ieee-wcci.org Chairs: Plamen P. Angelov, Lancaster University, UK p.angelov(a)lancaster.ac.uk Jose C. Principe, University of Florida, principe(a)cnel.ufl.edu Synopsis: Deep Learning is becoming a synonym of highly precise (reaching or surpassing capabilities of a human) computational intelligence technique. Very interesting and important results were reported recently in both scientific literature and also grabbed the imagination of the wider public and industry helping propel the interest towards AI, neural networks, machine learning. It was applied mostly to solve classification problems in image processing, but also for predictive tasks in speech processing and other problems. Despite the undoubted success in achieving high precision and avoiding handcrafting in feature selection a number of issues remain unresolved, such as: i) transparency and interpretability; ii) the requirement for extremely large training data set, computational resources and time; iii) overfitting and catastrophic failures with high confidence in some cases; iv) convergence proof for the case of reinforcement learning; v) rigid structure unable to be adapted/to dynamically evolve with new samples and/or new classes; vi)repeatability of the results. Methodologically, the vast majority of the techniques of this hot and quickly developing area are based exclusively on neural networks (convolutional, belief based, etc.). Very recently publications appear where the deep learning (multi-layer) architecture with different levels of abstraction is build based on fuzzy rulebased systems or fuzzy sets are used to represent coefficients/weights in Restricted Bolzman Machines, etc. The aim of the special session is to address the bottleneck issues listed above and discuss and represent alternative and most recent methods, techniques and approaches that can help resolve these issues. The specific sub-topics that will be of interest include: * Interpretable/Transparent Deep Learning * Computational and time complexity/efficiency of Deep Learning Methods * Repeatability of the results of Deep Learning Methods * Degree of confidence in the results of Deep Learning * Highly Parallelisable Deep Learning Methods * Deep Learning with proven convergence * Re-trainability and dynamically evolving structures/architectures for Deep Learning * Ensembles of Deep Learning Classifiers * Fuzzy Deep Rule-based Classifiers * Self-adaptive and Self-organising Deep Learning Architectures Also applications to: * Computer Vision * Image Classification * Robotics * Remote Sensing * Biology and Tomography * Surveillance and Defense * Industry 4.0 * Assistive Technologies and Digital Health Important dates: * Paper Submission Deadline 15 January, 2018 * Paper acceptance notification date 15 March, 2018 * Final paper submission deadline 1 May, 2018 Conference: 8-13 July, 2018 Submission Guidelines: Please follow the regular submission guidelines of WCCI 2018. Please notify the chairs of your submission by sending an email to: p.angelov(a)lancaster.ac.uk or principe(a)cnel.ufl.edu This special session is supported by the IEEE Task Forces on Deep Learning http://deeplearning.math.unipd.it/ and on Evolving and Adaptive Fuzzy Systems, http://www.caos.inf.uc3m.es/aefs/

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University of Sussex 4-year PhD Programme in Neuroscience
by Miguel Maravall 22 Nov '17

22 Nov '17

Dear comp-neuro colleagues, We are now inviting applications for the PhD Programme in Neuroscience at the University of Sussex, for entry in September 2018. Could you please kindly distribute to interested students - we are very interested in applications from students with quantitative (physical sciences/computing/math) backgrounds. Thank you Best wishes Miguel Maravall University of Sussex 4-year PhD Programme in Neuroscience Sussex Neuroscience is now inviting applications for September 2018 entry to our funded PhD Programme, which includes a first year of laboratory rotations and taught modules. These support a transition into neuroscience from other science disciplines such as physics and computing, and provide students with the opportunity to both broaden and deepen their experience of different neuroscience fields and techniques. More than 40 supervisors are offering research projects across the following thematic areas: Circuits, Systems and Computational Neuroscience Cognitive and Behavioural Neuroscience Cellular and Molecular Neuroscience Translational and Clinical Neuroscience Application Deadline: January 8th 2018 The Sussex campus is home to one of the largest neuroscience research communities in the UK, with strong interdisciplinary interactions between the biological and computational sciences. Our PhD Programme attracts some of the brightest students internationally. Home/EU fees are waived and a stipend is provided. We also welcome applications from non-EU students; we are able to contribute top-up funds to exceptional international students who have secured external funding. All students on the Programme can access financial support to attend conferences and additional training opportunities in the UK and overseas throughout their PhD. For further information and application instructions, please visit: www.sussex.ac.uk/sussexneuroscience/study/4yearphd<http://www.sussex.ac.uk/sussexneuroscience/study/4yearphd>

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a fantastic post-doc opportunity in the University of Cambridge
by Julija Krupic 22 Nov '17

22 Nov '17

Dear All, I am looking for talented and highly motivated researchers interested in studying how hippocampal spatial representations are generated and used for navigation. If you are interested please contact me directly krupiclab.com or apply here: http://www.jobs.ac.uk/job/BFR632/research-assistant-associate/ Best, Julija

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2018 Telluride Neuromorphic Cognition Engineering Workshop Call for Topic Proposals: Deadline 21.12.2017
by elisabetta chicca 22 Nov '17

22 Nov '17

The call for 2018 Telluride Neuromorphic Cognition Engineering Workshop Call for Topic Proposals is now open. The 2018 theme for the workshop is * Embodied Perception and Cognition*. Deadline for proposals is *21.12.2017*. See the call here: https://docs.google.com/document/d/11tdwIIcJ75NagH5ENyQrG05z2pGKEt9EGRTOSWB… We look forward to your proposals. Regards, The 2018 Telluride Workshop Organizing Team -- Prof. Dr. Elisabetta Chicca CITEC - Bielefeld University Inspiration 1 33619 Bielefeld - Germany Tel.: +49 521 106-12043 Fax : +49 521 106-12348

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Postdoctoral position in Human Single Unit and Intracranial EEG to study Human Memory
by Zaghloul, Kareem (NIH/NINDS) [E] 22 Nov '17

22 Nov '17

Hi, I would like to post the following advertisement for an available post-doc position to the comp-neuro listserv. If you could help me with that, I would appreciate it. Please let me know if you need any more information. Thank you for your help, Kareem Kareem A. Zaghloul, MD, PhD Surgical Neurology Branch National Institute of Neurological Disorders and Stroke, NIH Bldg 10, Rm. 3D20 10 Center Drive Bethesda, MD 20892-1414 O: 301-594-8114 F: 301-402-0380 The National Institute of Neurological Disorders and Stroke is seeking a full-time post-doctoral position focused on understanding the neural correlates of human memory. This position involves studies focused on analyzing and manipulating human intracranial electrophysiological signals, including single-unit activity, local field potentials, and electrocorticography (ECoG), captured from patients with medically refractory epilepsy and from patients receiving deep brain stimulation surgery. Post-doctoral fellows will join a laboratory aimed at understanding the neural mechanisms that underlie human episodic memory formation and decision making and at developing novel and innovative techniques to directly communicate with those circuits. We are seeking candidates that are highly creative, motivated, and independent with a Ph.D. in neuroscience, biomedical engineering, or a related field. Candidates must have a strong research background, with a record of relevant publications. Candidates will be encouraged and expected to participate in independent laboratory research, and will be expected to write scholarly manuscripts. Candidates must be able to lead and work well in a team. Candidates should have strong computational, quantitative, and/or engineering skills, with proficiency in developing custom code (Matlab, Python, etc.) for data analysis preferred. Past medical research is not required, but candidates must be willing to perform experiments in a clinical setting. Candidates will interact with clinical staff, graduate students, research fellows, and must have excellent spoken and written English skills. Applicants who will be attending either the Society for Neuroscience (Washington, DC), or American Epilepsy Society (Washington, DC) conferences can arrange for a meeting with the Principal Investigator, Dr. Kareem Zaghloul. Applicants should submit a brief statement of research activities and interests, a current CV, and names and contact information of at least three references. Salary will be commensurate with experience and accomplishments. To arrange a meeting with the PI and to send materials required for consideration for this appointment please contact Dr. Zaghloul at: zaghloulka(a)mail.nih.gov<mailto:zaghloulka@mail.nih.gov> NIH, an agency of DHHS, is an equal opportunity employer. All employees are subject to background investigation.

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[jobs] Fully funded MS/PhD student positions in Data Science, Bio-inspired Robotics, and Neural Engineering at IST, VISTEC, Thailand
by Poramate Manoonpong 21 Nov '17

21 Nov '17

Dear Colleagues, The School of Information Science and Technology (IST) at Vidyasirimedhi Institute of Science and Technology (VISTEC), Thailand, welcomes all applicants for our international Master's and Doctoral degree program. Our school offers a competitive, English language, interdisciplinary, world-class PhD training and research program in Information Science and Technology. We have 20 fully funded Master and PhD student positions. Our program includes 2-years MS, 5-years MS+PhD, and 3-years PhD options. The students will be formally affiliated with the Master/PhD program at IST, VISTEC, Thailand. They will have the opportunity to develop new algorithms and research ideas and perform experiments on real hardware, e.g., High performance computing, Advanced robotic systems, Exoskeleton, and Brain computer interface systems. Our basic research under the IST umbrella focuses on main areas: Data Science, Cloud/HPC, IOT, Bio-inspired Robotics, and Neural Engineering. Data Science and Engineering (Large-Scale Analytics, Data Engineering, Data Mining, Artificial Intelligence and Machine Learning): We address various scalability issues in machine learning, data mining, database query processing. We are especially interested in developing solutions for machine learning problems with an extremely large number of classes and a scalable system for managing and storing various forms of high-dimensional data. Our application domains include (but not limited to) natural language processing, time series data management, geospatial data mining, business intelligence, IoT data analytics, and health data analytics. Bio-inspired robotics: We address how to develop brain-like mechanisms for adaptive motor control and autonomous learning of embodied multi-sensorimotor robotic systems (i.e., bio-inspired robots, exoskeleton). We also transfer the developed mechanisms (BRAIN technology) to application areas like human-machine interaction, brain-machine interface, and rehabilitation (see www.brain.vistec.ac.th<http://www.brain.vistec.ac.th/> for more details). Neural Engineering: We address an investigation of closed-loop EEG-based Brain Computer Interface (BCI) helps bridge the gap in communication between man and machine. Understanding patterns of brain activity from basic neuroscience research will help engineering to optimize the BCI system that could be applied in the real-world environment. Advanced signal processing techniques and pattern recognition methods such as machine learning, artificial neural network, and deep learning can improve the efficiency of BCI by increasing information transfer rate and accuracy. Ultimately, research based on BCI could lead to the development of novel tools used in both clinical and healthy populations (see www.brain.vistec.ac.th<http://www.brain.vistec.ac.th/> for more details). Financial Support: This studentship includes 1) fee bursary to cover the tuition fee rate 2) a maintenance allowance during the study, 3) grant of 1 Million Bath scholarship for international research experience. Person Specification: The successful applicant from any nationality will have a strong undergraduate (first class or upper second class) and/or Master's degree in 1) Science (Physics, Mathematics, Computer and related fields) 2)Engineering (Computer, Mechanical, Electrical, Robotics, and related fields) 3) Applied Science (Information Technology, ICT, Machine Learning, and related fields) Applicants with excellent programming and analytical/mathematical skills as well as expertise and research interests lying at the intersection of Data science, Bio-inspired Robotics, and Neural Engineering are particularly welcome to apply. Applicants from non-English speaking countries will need to satisfy English language entry requirements. Application Documents: 1. CV 2. Official Transcripts 3. Statement of Purpose/ Statement of research interest Optional: 4. Letters of recommendation 5. English test score (TOEFL, IELTS, or other tests) 6. Publications, awards & honors 7. Portfolio and other relevant documents Applications should be submitted online by January 31st , 2018. http://www.vistec.in.th/admission/form.php http://www.vistec.in.th/admission/ For further information or questions please contact Box Leangsuksun E-mail: chokchai.l(a)vistec.ac.th<mailto:chokchai.l@vistec.ac.th> Vidyasirimedhi Institute of Science and Technology, Wangchan Valley 555 Moo1 Payupnai, Wangchan, Rayong 21210 Thailand Tel: +6633-01-4116 Website of VISTEC: http://www.vistec.ac.th<http://www.vistec.ac.th/>

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Multiple academic positions in Cognitive Analytics Research Laboratory, Ulster University
by Wong-Lin, Kongfatt 21 Nov '17

21 Nov '17

Several academic positions in data analytics, including neuroinformatics, are available at Ulster University. They range from Lecturership (Assistant Professorship equivalent) to (Full) Professorship. The application deadline is 8 December 2017. Best, KongFatt Wong-Lin https://www.ulster.ac.uk/staff/k-wong-lin ----------------------------------------------------------------------- Professor of Data Analytics (2 posts)<https://atsv7.wcn.co.uk/search_engine/jobs.cgi?SID=amNvZGU9MTY5MTM4MCZ2dF90…> http://www.jobs.ac.uk/job/BFM233/professor-of-data-analytics-2-posts/ Readers/Senior Lecturers in Data Analytics (3 posts)<https://atsv7.wcn.co.uk/search_engine/jobs.cgi?SID=amNvZGU9MTY5MTM4MSZ2dF90…> http://www.jobs.ac.uk/job/BFM247/reader-senior-lecturer-in-data-analytics-3… Lecturers in Data Analytics (3 posts)<https://atsv7.wcn.co.uk/search_engine/jobs.cgi?SID=amNvZGU9MTY5MTM4NCZ2dF90…> http://www.jobs.ac.uk/job/BFM258/lecturer-in-data-analytics/ Ulster University – Cognitive Analytics Research Laboratory, Faculty of Computing, Engineering and the Built Environment An exciting opportunity to contribute to internationally recognised research and help shape the future of data analytics. Ulster is a university in the top 3% globally, where excellence in teaching is underpinned by world-leading research. Ranked as one of the world’s top 150 young universities and in the top 25% of UK universities for overall research, Ulster is ambitious, forward-thinking and outward-looking. Our new Cognitive Analytics Research Laboratory is Northern Ireland’s first data analytics institute. It is a £4 million investment that brings together businesses, government and advanced academic research expertise to find innovative application areas for cognitive analytics techniques. It is part of an exciting programme of investment in new infrastructure and initiatives driven by a five-year strategic vision to deliver a university that is sustainable and innovative with a strong international reputation. Ulster has a long history of expertise in data analytics in both machine learning algorithms and the application of analytical techniques across a diverse range of domains including Health and Neuroinformatics. We are seeking to appoint talented and creative people with a genuine passion for their work, who will deliver outstanding research and teaching that encourages innovation, leadership and vision. The appointment is permanent and is open to applications from individuals or teams. Location: Magee campus, Derry~Londonderry. Attractive reward package including a competitive starting salary, pension scheme and financial assistance with relocation. Closing date for applications: 8 December 2017. For more information about this opportunity visit: www.ulster.ac.uk/jobs<http://www.ulster.ac.uk/jobs> ------------------------------------------------ This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Postdoctoral position in computational neuroscience and machine learning
by Maxim Bazhenov 20 Nov '17

20 Nov '17

Applications are invited for a post-doctoral research position in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to develop neuroscience inspired machine learning algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge ofneuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

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