- Comp-neuro - lists.cnsorg.org

Faculty position at CHAIN: Assistant Professor or Lecturer

by Hideaki Shimazaki

Dear colleagues, Our newly established Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) at Hokkaido University in Japan invites applications for a faculty position at the Assistant Professor or Lecturer level. The full description and details are attached below. See also: https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D120050453&ln_jor=1 https://www.chain.hokudai.ac.jp/?lang=en The deadline for applications is 8 June 2020 (JST). All the best, Hideaki --- Hideaki Shimazaki, Ph.D https://www.neuralengine.org Position Open: Assistant Professor or Specially Appointed Lecturer, Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, in Hokkaido, Japan invites applications for a 3.5 year research and teaching position with an anticipated start date of September 1st, 2020. The successful applicant will be appointed as a faculty member at the rank of Specially Appointed Assistant Professor or Lecturer in CHAIN. Women and members of other underrepresented groups are particularly encouraged to apply. CHAIN is a research and education center for interdisciplinary studies in the humanities, social sciences, neuroscience, and artificial intelligence. It aims to open up new directions of research into the nature of human existence by fostering interaction and collaboration between humanities and the social sciences, including philosophy, ethics, psychology (cognitive and social), law, and economics, and the natural sciences, such as neuroscience, AI, and cognitive science. In particular, it focuses on connecting philosophical ideas with methods and insights of mathematical and empirical sciences. A new interdisciplinary graduate program of CHAIN starts in July 2020. Qualifications The ideal applicant will have an independent research project that will strengthen and complement existing interdisciplinary research in CHAIN. They are expected to demonstrate the following qualities and characteristics: 1. A PhD by the time of the appointment in one (or more) of the following area(s): philosophy, ethics, psychology, cognitive science, neuroscience, AI, information science, or robotics. 1. Outstanding publication records and/or demonstrable potential to publish in highly esteemed publication outlets. 1. Strong motivation to fulfill research, teaching, and administrative duties as a faculty member in CHAIN. 1. Enthusiasm and competence for delivering postgraduate and undergraduate courses on topics pertinent to CHAIN’s research and education goals. 1. A demonstrated ability and strong interest to develop and engage in interdisciplinary research projects in collaboration with existing members of the institution. Application materials Submit the following materials, compiled in a single ZIP file, via email at jobs [at]chain.hokudai.ac.jp to complete your application: 1. Curriculum Vitae* 2. Summary of past research accomplishments (1-2 pages) 3. Three most important publications relevant to this position. 4. Brief statement of research and teaching interests (1-2 pages) 5. Two references (Names and contact details) Use common fonts such as Times New Roman in black and size 12 points. Submit each publication in a separate PDF file. Compile all the rest (1, 2, 4, and 5) in a single PDF file. This makes four PDF files in total, which must then be compiled in a single ZIP file. Submission is due Monday, 8 June, 2020 (JST). The subject line of the email must read “Application (Lecturer/Assistant Professor).” You will receive a confirmation email shortly after making a submission. Please contact us immediately if you did not receive one within 3 business days. Personal information obtained through these materials will only be used within this selection process. *Applicants who have been employed by Hokkaido University after April 1, 2014 (in any position, including Part-time Lecturer, Teaching Assistant, Teaching Fellow, Research Assistant and Short-term Support Assistant, etc.) should provide full details of their employment history in the CV. Appointment terms This is a full-time research and teaching position with an anticipated start date of September 1st, 2020. The salary will be paid under the annual-salary scheme and the discretionary labor system. The annual salary is determined in accordance with the internal regulations of Hokkaido University. Upon employment, one will be enrolled in the Ministry of Education, Culture, Sports, Science and Technology Mutual Aid Association, Employees Pension, Workers’ Accident Compensation Insurance and Employment Insurance. A one month probationary period applies. Questions about the position should be addressed to the chair of the search committee, Shigeru Taguchi (inquiry[at]chain.hokudai.ac.jp). Further information Website: www.chain.hokudai.ac.jp/?lang=en Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN) Hokkaido University Kita 12 Nishi 7, Kita-ku, Sapporo Hokkaido 060-0812 Japan Application submission: jobs [at] chain.hokudai.ac.jp Inquiries: : inquiry [at] chain.hokudai.ac.jp

May 15, 2020

PhD position in computational neuroscience and robotics

by Xavier Hinaut

A PhD position is available at the Inria Bordeaux Sud-Ouest center and the Institute of Neurodegenerative Disease in Bordeaux, France. What: PhD position in computational neuroscience and robotics Where: Inria, Bordeaux, France When: October 2020 (3 years duration) Who: Xavier Hinaut & Frédéric Alexandre Application deadline: May 22th (22/05/2020) How to apply: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Title of the PhD topic ================= NewSpeak: Neuro-computational models of language comprehension and production grounded in robots Keywords ================= Recurrent Neural Network (RNN), Reservoir Computing, Developmental Language Learning, Neuro-Robotics, Multimodal Language Grounding, Computational Neuroscience, Reinforcement Learning Candidate profile ================= - Good background in maths and computer science; - A strong interest for neuroscience and the physiological processes underlying learning; - Python programming with experience in scientific libraries Numpy/Scipy (or similar coding language: matlab, etc.); - Experience in machine learning or data mining is a preferred; - Independence and ability to manage a project; - Good English reading/speaking skills. Proposed research ================= We target to embody models into robots that will developmentally ground language. The grounding of semantics should come from the robot experiencing the world through its interactions with humans and the physical world. The goals are (1) to test hypotheses with biologically plausible language learning models with the Nao robot, (2) to extend the current model with unsupervised training and by reinforcement learning, and (3) to propose a new kind of Generative Adversarial Networks (GANs) for developmental language learning conditioned by grounded modalities such as vision. In order to model how a sentence can be processed, word by word (Hinaut & Dominey 2013) or even phoneme by phoneme (Hinaut 2018), the use of recurrent (artificial) neural networks, such as Reservoir Computing, offers interesting advantages. In particular the possibility to compare the dynamics of the model with data from neuroscience experiments (EEG, fMRI, ...). This paradigm allows to learn with few learning examples, and offers negligible runtime for human-robot interactions. The use of linguistic models with robots is not only useful to validate the models in real conditions, it also allows to test other hypotheses, notably on the anchoring of the language or the emergence of symbols. This involves finding out how a learning agent can link and categorise physical stimuli (vision, hearing, proprioception, etc.) to make the correspondence with symbols (Harnard 1990), or even to make these symbols emerge from stimuli coming from sensors (Taniguchi et al. 2016). We aim that a robot could process language from morphemes to sentences, similarly as a child, in order to better model how children acquire language. One aim is to obtain symbolic representations that are a composition of multimodal grounded representations. We will experiment how the newly developed language model will be able to learn to understand utterances by exploring which meanings the morphemes, words, ... can have based on other modalities of the robot (e.g. vision, proprioception). Starting from preliminary results (Juven & Hinaut 2020), we will first consider merging the representations from vision with a pre-trained CNN (Convolutional Neural Network). Then, reinforcement learning experiments will explore how the robot can learn the meaning of sentences: first by doing random actions for any user utterance, and then bootstrap from the user’s feedback. We will use a concrete corpus of sentences based on actions a robot can do (Hinaut & Twiefel 2019). We will implement several variants of language models: (1) extension of the reservoir computing model linked with grounded CNN, (2) adapt such model to the GAN paradigm in order to couple language comprehension and production in a self-learning generative mechanism (thus creating more biologically plausible GANs), (3) explore unsupervised (cross-situational learning) and reinforcement learning with these models. In parallel, we will adapt models features and behaviours to the ones observed in language acquisition experiments in psychology, and neural evidences in neuro-linguistic studies. In particular, we will explore how the models could shed light on language developmental impairments. We will run models in simulated humanoid robots and in a Nao robot. More information ============ More information is available on the application web page: https://jobs.inria.fr/public/classic/en/offres/2020-02637 Questions can be asked by email to Xavier Hinaut (xavier.hinaut(a)inria.fr) Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

May 15, 2020

Postdoc position in the Mainen lab at Champalimaud

by Luca Mazzucato

Systems Neuroscience Postdoctoral Fellow The Champalimaud Foundation, a private, non-profit research institution, is opening a call for a post-doctoral researcher, within the scope of the research project entitled "Neural mechanism of value based decision making of staying or leaving - Deciding when to initiate locomotion to move to the next reward location." This position involves data analysis/modeling of foraging behavior and self-initiated movements in rodents, related to a Systems Neuroscience experiment addressing the following question. When interacting with a complex environment, animals generate naturalistic behavior in the form of action sequences. To analyze and classify such behavior from video recordings is a computationally demanding task, requiring development of specific software pipelines adapted for big data structures using deep learning methods and state space models. This project aims at creating such a pipeline for analyzing videos of mouse behavior previously collected in the Mainen Lab at the Champalimaud Center for the Unknown, Portugal. In the experiment, animals performed certain action sequences, with variable onsets timing, leading to a water reward. Optogenetics photostimulation of inhibitory neurons in secondary motor regions was also performed during selected action sequences. Behavior during this task was recorded with two high speed, high resolution cameras pointing at the animal's face and front limbs. The large size of the datasets generated in this experiment (~1 Tb per animal, for 10 animals) requires an extensive effort to classify behavioral motifs. In the second part of the project, behavioral motifs will be related to large scale recordings of neural activity from Neuropixel probes. The fellow will investigate the relationship between neural activity and behavior using state space models and mechanistic models based on recurrent neural networks. The fellow will integrate a dynamic team of researchers as part of an international collaboration between the Mainen Lab <https://mainenlab.org/> at the Champalimaud Centre for the Unknown and the Mazzucato Lab <https://www.mazzulab.com/> at University of Oregon. National, foreign and stateless candidates can develop the proposed work remotely where team interaction is supported by online platforms (e.g. slack, zoom, etc). *References:* Recanatesi, S. et al., biorxiv (2020). Vertechi, P. et al., Neuron (2020). Murakami, M. et al., Neuron (2017). Murakami, M. et al., Nat. Neuro (2014). Essential qualifications: PhD in Neuroscience, Cognitive Science, Biology, Experimental Psychology, Engineering, Physics, Mathematics, or other areas relevant to neurophysiology and animal behavior; Proficiency in Python and Matlab programming language and familiarity with object oriented programming; Familiarity with Deep Learning software (TensorFlow); Familiarity with data analysis of biological experiments; Ability to work independently and troubleshoot technical issues; Good capacity and value for teamwork and communication skills; Fluency in English. REMUNERATION The monthly remuneration to be attributed is the 33rd level of the single remuneration table (TRU), approved by Portaria nº 1553-C/2008, of December 31st, starting at a base gross salary of 2,128.34 Euros. SELECTION PROCESS Applications will be accepted until June 15th, 2020 or until a qualified candidate is hired. Candidates must submit a single document (maximum 4 pages; paper or PDF file) that contains a motivation letter and the Curriculum Vitae, both written in English. Email applications must be addressed to careers(a)research.fchampalimaud.org and include “CPD2020-LOCODECISION” in the subject line. The selected candidate must submit proof of her/his PhD or Doctoral Degree within 10 days following notification of the preliminary results. More information about Diplomas recognition may be found in the Euraxess portal <http://www.euraxess.pt/portugal/information-assistance/recognition-diplomas> . All candidates who formalize their application incorrectly or who fail to provide the requirements imposed by this tender are excluded from admission. In case of doubt, the panel is entitled to request further documentation to support candidate statements. Notification of Results: The highest scoring candidate will be notified by email or telephone. All other candidates will be notified solely by email. Non-discrimination and equal access policy: The Champalimaud Foundation actively promotes a policy of non-discrimination and equal access, so that no candidate can be privileged, benefited, harmed or deprived of any right, on basis of age, sex, sexual orientation, marital status, family status, economic situation, education, social origin or condition, genetic heritage, reduced working capacity, disability, chronic illness, nationality, race, territory of origin, language, religion, political or ideological convictions, and trade union membership.

May 14, 2020

Call for 22 PhD positions in BioRobotics at the BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy

by Calogero Maria Oddo

************************************* 22 PhD positions in BIOROBOTICS open! https://www.santannapisa.it/sites/default/files/flyer_phd_biorobotica_2020_…. ************************************* The PhD Program in BioRobotics is a three-year course managed by the BioRobotics Institute (http://sssa.bioroboticsinstitute.it) in the Department of Excellence in Robotics & AI, at Sant’Anna School of Advanced Studies, in Pisa (Italy). The PhD in BioRobotics is one of the largest doctoral schools worldwide in biomedical engineering and robotics, with about 100 PhD students enrolled. All positions are fully funded by Sant'Anna and the Italian Institute of Technology.The number of positions awarded could be expanded with additional fellowships that may be available before the start of the PhD course in October 2020. The students are educated in a stimulating and multidisciplinary environment, both through high-level courses and through demanding, creative and original research work. PhD projects are carried out in very well equipped, state-of-the-art laboratories (in such fields as micro-engineering, biomedical engineering, biomimetic and soft robotics, rehabilitation technologies, surgical robotics and neural engineering, robot companions) and through individual and team work performed under the supervision of a full-time faculty. ADMISSION: Students are admitted to the PhD Program following a successful entrance examination. Eligible applicants must hold a Master of Science (M.Sc.) degree or equivalent. Undergraduate students may also apply if they graduate within Oct. 31, 2020. START: Oct. 1, 2020 CALL details: https://www.santannapisa.it/en/admissions/call-admission-phd-biorobotics-3 APPLY at: www.santannapisa.it/en/education/phd-biorobotics DEADLINE: June 3, 2020 CONTACT: PhDBiorobotics(a)santannapisa.it Best regards, Calogero Oddo, on behalf of the PhD Board -- Calogero M. Oddo PhD BioRobotics, MSc and BSc Electronic Engineering Associate Professor of Bioengineering https://www.santannapisa.it/en/calogero-maria-oddo Vice-Coordinator of the PhD programme in BioRobotics Sant'Anna School of Advanced Studies, Pisa, Italy https://www.santannapisa.it/en/education/phd-biorobotics Head of the Neuro-Robotic Touch Laboratory, Neuro-robotics Area, The BioRobotics Institute Viale Rinaldo Piaggio 34, 56025, Pontedera (PI), Italy Sant'Anna School of Advanced Studies, Pisa, Italy http://www.santannapisa.it/en/neuro-robotic-touch-laboratory Department of Excellence in Robotics & AI Sant'Anna School of Advanced Studies, Pisa, Italy Piazza Martiri della Libertà, 33 - 56127 Pisa, Italy https://www.santannapisa.it/en/robotics-ai IEEE Senior Member, Founding Vice-Chair of the Italian Chapter of the IEEE Sensors Council (2018-20) http://sites.ieee.org/italy-sensors/about-ieee Office: +39050883067; Mobile: +393316992273; email:calogero.oddo@santannapisa.it -- Questa e-mail è stata controllata per individuare virus con Avast antivirus. https://www.avast.com/antivirus

May 13, 2020

Visiting Assistant Professor Position in Applied Mathematics at Northwestern University

by William L. Kath

Visiting Assistant Professorship in Applied Mathematics The Department of Engineering Sciences and Applied Mathematics at Northwestern University invites applications for the position of Visiting Assistant Professor in Applied Mathematics. This is a one-year, non-tenure-track position with the possibility of renewal for a second year. Duties involve teaching and research in applied mathematics with a focus on applications in engineering and/or the sciences. More information about this position can be found at: https://www.mccormick.northwestern.edu/applied-math/open-positions.html The Department seeks outstanding candidates who have received a Ph.D. degree in applied mathematics, engineering, physics or another applied math-related discipline, or who expect to do so by July 2020, and who aspire to engage in independent and interdisciplinary research and teaching. The starting date is September 1, 2020. The application package should include a cover letter, curriculum vita, statement of research accomplishments and interests, statement of teaching experience and philosophy, and if available a representative manuscript (published, submitted or in preparation). The application should be submitted online at: https://facultysearch.mccormick.northwestern.edu/apply/index/MTAz In addition, the applicant should arrange for at least two, but no more than three letters of recommendation addressing both research and teaching qualifications. Recommendation letters will be automatically solicited from the letter writers by email after the names are entered in the online application system. Questions may be directed to Meelee Ahn Park at meelee.park(a)northwestern.edu <mailto:meelee.park@northwestern.edu> (Subject line: Visiting Assistant Professor Search). To ensure full consideration, applications should be received by May 15th, 2020, but applications will be accepted until the position is filled. Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States. Engineering Sciences and Applied Mathematics Northwestern University 2145 Sheridan Road, Room M426 Evanston, IL 60208-3125, USA esam(a)northwestern.edu <mailto:esam@northwestern.edu> Phone: (847) 491-3345 -- William L. Kath Co-Director, NSF-Simons Center for Quantitative Biology Professor, Engineering Sciences and Applied Mathematics McCormick School of Engineering, Northwestern University 2145 Sheridan Road, Evanston, IL 60208-3125 Phone: 847-491-8784 Fax: 847-491-2178

May 13, 2020

International Symposium on Artificial Intelligence and Brain Science 2020 in Tokyo

by Kenji Doya

We are pleased to announce a symposium that brings together researchers in the forefront of AI and neuroscience. Application for poster presentation is open till June 1st and general registration will start from July 1st, 2020. ******** International Symposium on Artificial Intelligence and Brain Science Date: October 10-12 (Sat-Mon), 2020 Venue: Ito Hall, The University of Tokyo, Japan Web site: http://www.brain-ai.jp/symposium2020/ Program (it may be held online depending on the COVID-19 situation) • Saturday, October 10th (from 1pm) Keynote: Josh Tenenbaum (MIT) Session 1: Deep Learning and Reinforcement Learning Yann LeCun (NYU, Facebook), Yutaka Matsuo (U Tokyo), Doina Precup (McGill U) David Silver (DeepMind), Masashi Sugiyama (RIKEN AIP/U Tokyo IRCN) • Sunday, October 11th Session 2: World Model Learning and Inference Ila Fiete (MIT), Karl Friston (UCL), Yukie Nagai (U Tokyo IRCN) Maneesh Sahani (Gatsby Unit), Tadahiro Taniguchi (Ritsumeikan U) Poster Session Session 3: Metacognition and Metalearning Matthew Botvinick (DeepMind), Ryota Kanai (ARAYA), Angela Langdon (Princeton U) Hiroyuki Nakahara (RIKEN CBS), Xiao-Jing Wang (NYU) • Monday, October 12th Session 4: AI for Neuroscience and Neuromorphic Technologies Jim DiCarlo (MIT), Yukiyaku Kamitani (Kyoto U), Rosalyn Moran (King’s College London) Terry Sejnowski (Salk Institute), Hidehiko Takahashi (Tokyo MDU) Session 5: Social Impact and Neuro-AI Ethics Anne Churchland (CSHL), Kenji Doya (OIST), Arisa Ema (U Tokyo IFI) Hiroaki Kitano (SONY CSL), Stuart Russell (UC Berkeley) Poster Registration: May 11th - June 1st (review result notified by June 20) General Registration: July 1st - 31st (or when the capacity is reached) Please check the web site: http://www.brain-ai.jp/symposium2020/ Sponsor: KAKENHI Project on Artificial Intelligence and Brain Science (http://www.brain-ai.jp) Co-sponsors: RIKEN AIP (https://aip.riken.jp/?lang=en) U Tokyo IFI (https://ifi.u-tokyo.ac.jp/en/) U Tokyo IRCN (https://ircn.jp/en/) Contact: ncus(a)oist.jp ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

May 13, 2020

Dual-award PhD in Neuromorphic Olfaction (UH/WSU)

by Michael Schmuker

We’re looking for an outstanding candidate to enter a Dual-PhD programme on Neuromorphic Olfaction. The successful candidate will pursue a PhD in the BioMachineLearning lab at the University of Hertfordshire (UK), and the International Centre for Neuromorphic Systems (ICSC), at Western Sydney University, Australia. The successful candidate will develop event-based algorithms for Neuromorphic olfaction, in close collaboration with Neuromorphic hardware developers and computational neuroscientists. In this unique opportunity, the candidate is eligible to obtain a PhD award from both universities, UH and WSU. It’s a fully funded programme that covers also travel expenses between UH and WSU. Interested? Get in touch! More info: https://biomachinelearning.net/positions <https://biomachinelearning.net/positions> — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire https://biomachinelearning.net <https://biomachinelearning.net/>

May 12, 2020

[jobs] Postdoctoral position in: Cognition for safety and ergonomics for human-robot interaction in manufacturing workspaces - [ Postdoc ]

by Francesco Rea

The COgNiTive Architecture for Collaborative Technologies Research Line at Istituto Italiano di Tecnologia in Genoa - Center for Human Technologies, is opening one postdoctoral position focusing on the assessment of engagement with safety and ergonomic work, design of proactive measures and counter measures for safety preservation, optimization of ergonomics, design of software infrastructure for social interaction and safety-ergonomic preservation. The research activities will be carried out under the supervision of Dr. Alessandra Sciutti and Dr. Francesco Rea (Participant Manager within the Steering Board -SB). The selected candidate will work with a multidisciplinary consortium of participant to the awarded project APRIL (H2020, n. G.A. 870142). APRIL project aims at implementing and deploying market oriented, low cost and multipurpose robots that supports semiautomatic tasks in manufacturing production lines and handle flexible or deformable materials in industries of any size or domain. The candidate will work with different robotic platforms for human-robot interaction in manufacturing context selected together with the consortium and with different sensorial setups specifically designed to assess the gaze pattern, reaction time, working movements, fatigue level in workers. https://www.iit.it/careers/openings/opening/1198-postdoctoral-position-in-c… The activity will be carried out within the implementation of the APRIL project in a fully equipped laboratory, including motion capture and eye-tracking devices, and in a team with a variety of competences ranging from robotics to designing of experimental studies on humans. The research for this Postdoctoral position will involve: * Sensing of human working conditions for social, safe and ergonomic based activities on human-robot collaboration * Design of control systems for Safety in human-robot collaboration * Development of a system improving human-robot social collaboration in manufacturing context * Development of a system improving ergonomics and mitigating health and safety risks The first goal of the research is redesigning cognition for safety and ergonomics for human-robot collaboration in manufacturing workspaces. The second goal of technological implications is to support the design of new multipurpose robotics for manipulation of deformable materials in manufacturing processes. The successful candidate will be offered a salary commensurate to experience and skills. Interested applicants should submit CV, list of publications, name and contacts of 2 referees and a statement of research interest to jobpost.78417(a)iit.it<mailto:jobpost.78417@iit.it> by May 20, 2020 quoting Postdoctoral position in "Cognition for safety and ergonomics for human-robot interaction in manufacturing workspaces - CB 78417" in the subject line.

May 10, 2020

Research Assistant (Research Associate)

by Artur Luczak

Research Assistant (Research Associate) at the University of Lethbridge. Our lab seeks a highly motivated individual with a strong computational background to work at the interface of neuroscience and machine learning. We are especially interested in the application of deep neural networks to improve our understanding of neuronal data, and the application of recent neuroscience findings to improve the performance of deep neural networks. In our lab we also record the activity of hundreds of neurons in normal and epileptic animals, and the successful candidate is welcome to participate in those projects. Preferred candidate should have strong background in modeling neurons and networks, and should be very familiar with models of synaptic plasticity (e.g. BCM). Our lab at the Canadian Centre for Behavioural Neuroscience in the University of Lethbridge is located in the sunniest area of Canada and next to scenic Rocky Mountains. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. For more information please visit our website at: http://lethbridgebraindynamics.com/artur_luczak. Duties and responsibilities: - Conduct research and literature reviews, in related topics for use in scholarly publications. - Compile research results and assist professors in the analysis of results and the preparation of journal articles or papers. - Analyze data using statistics, programming techniques and artificial neural networks. - Develop analytical methods in biologically plausible artificial neural networks. - Participate in scientific discussion groups and seminars. All duties and responsibilities shall be carried out under the supervision of Prof. Artur Luczak. Skills & Qualifications: - Master degree’s in neuroscience, physics, computer science or related topics. - 3 years of related research work experience. - Having strong background in modeling neurons and networks, and should be very familiar with models of synaptic plasticity. - Familiarity with epilepsy is an asset - Highly experienced in programming with Python and Matlab. - Ability to work with data, applying machine learning methods and deep learning. - Working with computer clusters and cloud computing. - Excellent communication and team work skills. Working Conditions: Work in an office with a computer provided. Hours of Work: Full-time, 30-32 hours per week. Salary: $21.63 /hour Duration: one year with the opportunity for extension Language requirements: English Benefits: Standard benefits including Extended Health, Dental, EFAP, Life Insurance and Long Term Disability. Interested applicants are encouraged to contact Professor Artur Luczak (Luczak(a)uleth.ca) with a copy of their CV and a cover letter. Address: University of Lethbridge. 4401 University Drive West, Lethbridge, Alberta T1M 1R6, Canada

May 10, 2020

Call for papers MLCN at MICCAI 2020

by MLCN Workshop

*Please find below the call for papers for the International Workshop of Machine Learning in Clinical Neuroimaging (MLCN) on 4 October 2020 at MICCAI 2020 in Lima, Peru. We welcome contributions on novel machine learning methods and their applications to clinical neuroimaging data.* The submission deadline is *30 June 2020*, and all MLCN accepted papers will be eligible for the best paper award of 500 USD. For more information, please visit https://mlcnws.com/. Best wishes, The MLCN 2020 committee Christos Davatzikos Andre Marquand Jonas Richiardi Emma Robinson Ahmed Abdulkadir Cher Bass Mohamad Habes Seyed Mostafa Kia Jane Maryam Rondina Chantal Tax Hongzhi Wang Thomas Wolfers International Workshop on Machine Learning in Clinical Neuroimaging 4 October 2020 in Lima, Peru The International Workshop of Machine Learning in Clinical Neuroimaging ( https://mlcnws.com/) a satellite event of MICCAI (https://miccai2020.org) calls for original papers in the field of clinical neuroimaging data analysis with machine learning. The two tracks of the workshop include methodological innovations as well as clinical applications. This highly interdisciplinary topic provides an excellent platform to connect researchers of varying disciplines and to collectively advance the field in multiple directions. For the machine learning track, we seek contributions with substantial methodological novelty in analyzing high-dimensional, longitudinal, and heterogeneous neuroimaging data using stable, scalable, and interpretable machine learning models. Topics of interest include but are not limited to: - Spatio-temporal brain data analysis - Structural data analysis - Graph theory and complex network analysis - Longitudinal data analysis - Model stability and interpretability - Model scalability in large neuroimaging datasets - Multi-source data integration and multi-view learning - Multi-site data analysis, from preprocessing to modeling - Domain adaptation, data harmonization, and transfer learning in neuroimaging - Unsupervised methods for stratifying brain disorders - Deep learning in clinical neuroimaging - Model uncertainty in clinical predictions - ... In the clinical neuroimaging track, we seek contributions that explore how the application of advanced machine learning methods help us to move towards precision medicine for complex brain disorders. Topics of interest include but are not limited to: - Biomarker discovery - Refinement of nosology and diagnostics - Biological validation of clinical syndromes - Treatment outcome prediction - Course prediction - Analysis of wearable sensors - Neurogenetics and brain imaging genetics - Mechanistic modeling - Brain aging - ... Submission Process: The workshop seeks high quality, original, and unpublished work that addresses one or more challenges described above. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style (see https://www.miccai2020.org/en/PAPER-SUBMISSION-GUIDELINE.html#manuscript-fo… for detailed author guidelines) using the CMT system at https://cmt3.research.microsoft.com/MLCN2020. The page limit is 8-pages (text, figures, and tables) plus up to 2-pages of references. We review the submissions in a double-blind process. Please make sure that your submission is anonymous. Accepted papers will be published in a joint proceeding with the MICCAI 2020 conference. Best Paper Award: This year, all MLCN accepted papers will be eligible for the best paper award. The recipient of the award will be chosen by the MLCN scientific committee based on the scientific quality and novelty of contributions. The winner will be announced at the end of the workshop and will receive 500 USD honorarium. Important Dates: - Paper submission deadline: June 30th, 2020 - Notification of Acceptance: July 24th, 2020 - Camera-ready Submission: July 31st, 2020 - Workshop Date: 4 October 2020

May 8, 2020