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PhD Studentship in Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs
by Tsaneva-Atanasova, Krasimira May 25, 2018

May 25, 2018

PhD Studentship in Quantitative Pharmacology and Neuroscience: Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs University of Reading - School of Pharmacy Supervisors: Dr Francesco Tamagnini (Pharmacy), Dr Marcus Tindall (Mathematics & Statistics), Prof Krasimira Tsaneva-Atanasova (University of Exeter, College of Mathematics, Engineering and Physical Sciences). Project overview: Neurons work as information relays. They integrate information received from the environment at the subcellular scale, generating an appropriate electrophysiological response. The understanding of electrical processes happening at the plasma membrane level has been clarified by Hodgkin and Huxley, combining experimental recordings to mathematical modelling of equivalent electrical circuits. However, quantitative models describing the effects of cell signalling on the cellular response are lacking. Adenosine is a neurotransmitter binding both A1 (Gi) and A2 (Gs) receptors. A1 and A2 stimulation results in altered neuronal excitability via K+ permeability changes. In this project, we aim to combine a mathematical model of adenosine receptor signal transduction (Tindall) with the Hodgkin-Huxley model of a neuron (Tsaneva-Atanasova), to generate an in-silico multiscale model of electrophysiological response to chemical stimulation. We will test the predictive capability of the model with whole-neuron patch-clamp recordings (Tamagnini). The mathematical models formulated during the project will utilise the theory of differential equations (ordinary and partial) solved and analysed both numerically and analytically (e.g. dynamical systems theory, asymptotic methods). The successful candidate will be involved in the design and undertaking of wet laboratory experiments for informing the mathematical models. The final aim of this project is to develop and validate a software capable of predicting changes to an artificial neuron based on its exposure to varying concentrations of a given ligand. Eligibility: * Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent in Mathematics, Engineering or Neuroscience related subjects. The applicant will have a strong background in mathematics and computer coding (Matlab, Python, C++) and a keenness to engage with and learn wet lab techniques (i.e. pipetting, solution making, single cell electrophysiology); * This studentship is open to UK/EU students only. Funding details: * Starts 10/2018; * 3-year award; * Tuition fees plus stipend (Research Council UK 2018/19 rate is currently £14,777). How to apply: To apply for this studentship, please submit an application for a PhD in Pharmacy at http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply…. Important notes: 1. Please quote the reference ‘GS18-018’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your online application. 2. When you are prompted to upload a research proposal, please omit this step. Application deadline: 30th June 2018. Further enquiries: Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria. For further details, please contact: f.tamagnini(a)reading.ac.uk.<mailto:f.tamagnini@reading.ac.uk>

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Faculty position at UNAM Institute of Neurobiology (Mexico)
by Fidel Santamaria May 24, 2018

May 24, 2018

Computational and Genomic Neuroscience at UNAM The Institute of Neurobiology, UNAM (www.inb.unam.mx<http://www.inb.unam.mx>) invites applications for two tenure-track positions, one in Computational Neuroscience and another one in Genomic Neuroscience. We seek experienced scientists with proven record of publications to develop innovative research programs employing on-campus high performance computing resources to complement the current neuroscience research at the Institute. The successful applicants will be expected to establish externally funded research programs, to engage in intramural collaborative projects, to supervise undergraduate and graduate students, and to teach basic and advanced courses in their field of expertise. Applicants should send their CV, addresses of three references, a five-page research proposal and a one-page statement on their views on teaching to ataulfo(a)unam.mx<mailto:ataulfo@unam.mx>. The application deadline is August 15th, 2018. We encourage applications from women. Instituto de Neurobiología Universidad Nacional Autónoma de México Laboratorio de Neurobiología Molecular y Celular (D15) Juriquilla, Querétaro, QRO CP 76230 Tel. +52 (442) 238-1064 Email ataulfo(a)unam.mx<mailto:ataulfo@unam.mx> atanez(a)gmail.com<mailto:atanez@gmail.com> Skype atanez1

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Post-baccalaureate research position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience
by Yingxue.Wang＠mpfi.org May 23, 2018

May 23, 2018

*** Apologies for cross posting*** Post-Baccalaureate Research Experience Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for the post-baccalaureate research program. This one-year program provides research experience and exposure to students who have graduated from college and are planning to apply to graduate school. We seek highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent bachelor degree in neuroscience or related fields. Candidates holding a degree in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae - A statement of motivation and interests (1-2 pages) - Academic certificates and transcripts - The names and contact information of two references Please find more details about this program at https://www.maxplanckflorida.org/education/training-programs/pre/. The official application deadline has already passed. Please address the request directly to the above email address. Best regards, Yingxue Wang Research Group Leader Max Planck Florida Institute for Neuroscience

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Postdoctoral Position in Brain-Computer Interfaces
by Tomislav Milekovic May 23, 2018

May 23, 2018

The research group Dr. Tomislav Milekovic at the University of Geneva is offering a postdoctoral position financed by the Wyss Center for Bio and Neuroengineering and the Swiss National Science Foundation to work on restoring communication and independence of people with tetraplegia and locked-in syndrome using brain-computer interfaces. The successful applicant will work to develop and advance brain-computer interfaces based on electroencephalography (EEG) and intracortical microelectrode array recordings. The ideal candidate will have: 1. Experience in assembling and maintaining brain-computer interface systems 2. Leading brain-computer interface experiments with human or animal subjects 3. Experience in the quantitative analysis of electrophysiological neural signals (EEG, ECoG, LFP, spikes) 4. Background in computational/theoretical neuroscience, physics or mathematics 5. Experience in developing and using neural decoders 6. Experience in C/C++ software development The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of neuroscience, engineering and prosthetics. They will collaborate with several labs of the Campus Biotech in Geneva, and be strongly supported by the Wyss center for Bio and Neuroengineering led by Prof. John Donoghue. University of Geneva provides state-of-the-art facilities is one of the leading technical universities worldwide. In addition, University of Geneva offers competitive postdoctoral salaries ranking among the highest in the world. Applications including a CV and the statement of research interests should be sent to tomislav.milekovic(a)unige.ch<mailto:tomislav.milekovic@unige.ch>.

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Postdoc position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience
by Yingxue.Wang＠mpfi.org May 23, 2018

May 23, 2018

*** Apologies for cross posting*** Postdoctoral Fellow Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for postdoctoral positions. Our group seeks highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent Ph.D. or MD/Ph.D. in neuroscience or related fields. Candidates holding a Ph.D. in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is highly preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. We offer outstanding benefits and salary compensation above the NIH scales. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae with a list of publications - A statement of research experiences and interests (1-2 pages) - The names and contact information of three references Personal contact can be addressed to the above email address prior to the application.

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PhD studentships in Neuromorphic computing and Data Science
by Schmuker, Michael May 23, 2018

May 23, 2018

We are offering a several PhD studentships in the Biocomputation group at the University of Hertfordshire. Details here: https://www.herts.ac.uk/__data/assets/pdf_file/0007/209365/Data-Science-and… Our group translates processes from the brain into algorithms for efficient computing. A particular area of interest is Neural Data Science, where we extract information from complex data sets obtained in neuroscience. Our goal is to shed light on how the brain is processing information and to cast this knowledge into efficient algorithms for pattern recognition and signal processing. We implement such algorithms by leveraging so-called neuromorphic hardware, i.e., specialised computer chips that mimic the massively parallel architecture of the brain, which greatly accelerate brain-inspired neural computing. We are looking for highly motivated candidates with a keen interest in squeezing every bit of information out of complex data sets, to understand how the brain copes with the relentless onslaught of sensory information, and to implement those aspects on a new computer architecture. A diverse choice of topics is available, including but not limited to: • Data mining in neuronal imaging using matrix factorisation and machine learning • Brain-inspired pattern recognition using supervised and unsupervised learning • Olfaction-inspired signal processing and odor recognition for electronic gas sensors It is also possible to suggest topics. Candidates should have excellent programming skills and also some experience in data mining. Previous exposure to low-level hardware programming (e.g. microcontrollers, GPUs) and/or computer engineering is a plus. We collaborate with world-leading neuroscience labs in the UK and abroad to investigate how the brain is processing dynamic sensory information. As a member of the Human Brain Project we pioneer the use of neuromorphic hardware for Data Science. This guarantees a stimulating research environment for a project that aims not only at generating theoretical insight but also validating the findings with experimental scientists and pursuing applications in the real world. Successful candidates are eligible for a research studentship award from the University (approximately GBP 14,777 per annum bursary plus the payment of the standard UK student fees). Applicants from outside the UK or EU are eligible, but will have to pay half of the overseas fees out of their bursary. Please contact Principal Investigator Dr. Michael Schmuker prior to application to scope out a project proposal that is tailored to your background, via email: m.schmuker(a)herts.ac.uk. More info and instructions how to apply are available at https://www.herts.ac.uk/study/schools-of- study/computer-science/our-research/the-phd-programme-in-computer-science . The next short-listing process for studentship applications will begin on 25 June 2018. — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire http://biomachinelearning.net

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PhD position in systems/computational neuroscience, Leicester, UK
by Okun, Michael (Dr.) May 22, 2018

May 22, 2018

A PhD position is available at Centre for Systems Neuroscience, Leicester, UK. The project will focus on organisation and mechanisms of resting state cortical dynamics, particularly in the infraslow (0.01 - 1 Hz) timescales. Additional details are available at https://www.findaphd.com/search/ProjectDetails.aspx?PJID=97389 or by contacting Michael Okun (m.okun(a)le.ac.uk) The deadline for applications is 7th of June.

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OMG- Emotion Recognition Challenge - Final Results
by Pablo Barros May 22, 2018

May 22, 2018

Dear all, I would like to share with you all the results of our first OMG- Emotion Recognition Challenge. Our challenge is based on the One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset), which is composed of 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Each team had a task to describe each video with a continuous space of arousal/valence domain. The challenge had a total of 34 teams registered, from which we got 11 final submissions. Each final submission was composed of a short paper describing the solution and the link to the code repository. The solutions used different modalities (ranging from unimodal audio and vision to multimodal audio, vision, and text), and thus provide us with a very complex evaluation scenario. All the submissions were based on neural network models. We split results into arousal and valence. For arousal, the best results came from the GammaLab team. Their three submissions are our top 3 CCC arousal, followed by the three submissions from the audEERING team, and the two submissions from the HKUST-NISL2018 team. For valence, the GammaLab team stays still in first (with their three submissions), followed by the two submissions of ADSC team and the three submissions from the iBug team. Congratulations to you all! We provide a leaderboard on our website ( https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/ ), which will be permanently stored. This way, everyone can see the final results of the challenge, have a quick access to a formal description of the solutions and to the codes. This will help to disseminate knowledge even further and will improve the reproducibility of your solutions. We also provide a general leaderboard which will be updated constantly with new submissions. If you are interested in having your score in our general leaderboard, just send us an e-mail following the instructions on our website. I would also to invite you all to the presentation of the challenge summary during the WCCI/IJCNN 2018 in Rio de Janeiro, Brasil. Best Regards, Pablo -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

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Call for Papers: Special Session on Computational Methods for Neuroimaging Analysis, 6-8 September, Portugal
by Tiago Azevedo May 22, 2018

May 22, 2018

Dear all, Below find the call for papers for the special session "Computational Methods for Neuroimaging Analysis". It will be be held during the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, at Caparica, Portugal, from 6 to 8 September. **Important Dates** Paper submission deadline: 10 June 2018 Acceptance notification: 9 July 2018 Author registration due: 20 July 2018 Camera ready due: 29 July 2018 Conference: 6-8 September 2018 **Link** https://eventos.fct.unl.pt/cibb2018/pages/special-sessions **Aim and scope** There is an increasing need for the application of machine learning (ML) techniques which can perform image processing operations such as segmentation, coregistration, classification and dimensionality reduction in the field of neuroimaging. Although the manual approach often remains the golden standard in some tasks (like segmentation), ML can be utilised to automate and facilitate the work of researchers and clinicians. Frequently used techniques include support vector machines (SVMs) for classification problems, graph-based methods for brain network analysis and recently artificial neural networks (ANNs). Deep ANNs, i.e. deep learning, have proved to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the medical and neuroimaging domains for automatic disease diagnosis, tissue segmentation and even synthetic image generation. The issue, however, is the relative sample paucity in typical neuroimaging datasets which leads to poor generalisation considering the high number of parameters employed in typical deep neural networks. Consequently, parameter- efficient design paradigms ought to be created. Another approach to investigate degeneration is the study and mapping of the neural connections in the brain known as the connectome. The connectome can be seen as a matrix representing all possible pairwise connections between different neural areas. Researchers study both the structural and functional connectivity in order to understand important brain patterns, such as how the connectome impacts the dynamics of disease spreading, ageing and learning. Topics of interest includes but are not limited to: • Machine learning techniques for segmentation, coregistration, classification or dimensionality reduction of neuroimages   • Deep learning for neuroimaging analysis   • Brain network analysis   • Applications of graph theory to MRI and fMRI data   • Applications of machine learning methodologies for neurodegenerative disease studies   • Computational modelling and analysis of neuroimaging   • Methods of analysis for structural or functional connectivity   • Development of new neuroimaging tools **Session chairs** Tiago Azevedo, University of Cambridge, UK Giovanna Maria Dimitri, University of Cambridge, UK Pietro Liò, University of Cambridge, UK Angela Serra, University of Salerno, Italy Simeon Spasov, University of Cambridge, UK

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Two postdoc positions at Champalimaud Centre for the Unknown, Lisbon
by Christian Machens May 21, 2018

May 21, 2018

POSTDOC POSITIONS IN COMPUTATIONAL / SYSTEMS NEUROSCIENCE Two postdoctoral positions - one in theory and one in experiment - are available in a joint project between the labs of Alfonso Renart and Christian Machens at the Champalimaud Centre for the Unknown in Lisbon, Portugal. Location: The Champalimaud Centre for the Unknown is situated on the waterfront in central Lisbon. English is the official language of the Centre. The center is composed of about 20 main research groups who study diverse topics in neuroscience using advanced, cutting edge techniques. Project: The proposed project will investigate to what extent neural circuits actively compensate random perturbations. The project involves the recordings and partial silencing of neural populations, population-level analysis using dimensionality reduction and other techniques, and the modeling of the results with spiking networks. Relevant background literature: Renart, de la Rocha, et al (2010), Science 327:587-90; Barrett et al (2016), eLife 5:12454; Deneve and Machens (2016), Nat Neurosci 19:375-82. Profile (theory): The ideal candidate should have a PhD with a strong, quantitative background (ideally in fields such as machine learning and/or computational neuroscience). The position is funded for two years with possibility of extension. Profile (experiment): The ideal candidate should have experience in electrophysiology (e.g. recordings from behaving head-fixed mice) and data analysis (e.g. dimensionality reduction methods etc). Applications should include a CV, a statement of research interests (max 1 page), and two letters of recommendation. Feel free to ask any informal questions about the positions if you are interested. Electronic submissions in pdf-format are preferred and should be send to both of the following email addresses: christian.machens(a)neuro.fchampalimaud.org alfonso.renart(a)neuro.fchampalimaud.org

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