- Comp-neuro - lists.cnsorg.org

New Master’s programme Applied Data Science in Göttingen, Germany

by Ecker, Alexander

*New Master’s program Applied Data Science in Göttingen, Germany* https://uni-goettingen.de/msc/datascience In the upcoming winter term, we are launching the new international Master’s programme Applied Data Science at the University of Göttingen. The study programme is characterised by its interdisciplinary nature. Students holding a Bachelor’s degree in data science, computer science or mathematics are welcome, as well as graduates from other fields. We want to equip students with both in-depth knowledge of the key mathematical, statistical and computer science methods for Data Science as well as to make sure they understand how to use these methods in an application domain. Currently, the following application domains can be chosen: Computational Neuroscience, Bioinformatics, Medical Data Science, and Digital Humanities. The Göttingen Campus features an amazing variety of data-intensive research from natural and life sciences to social science and humanities. It includes top-notch research institutions like five Max Planck Institutes, the German Primate Center and the German Aerospace Center. Göttingen a university town located in the centre of Germany and Europe, in a region known for its green hills, lovely small towns with half-timbered houses and the Harz Mountains. Well-connected through motorways and high-speed trains, it is a great place to discover Germany and Europe. For further information see https://uni-goettingen.de/msc/datascience or the flyer: https://owncloud.gwdg.de/index.php/s/gBeb11Io6mw9XiR

April 29, 2021

WWNeurise series on naturalistic behavior & applications/recommendations

by William Podlaski

WorldWideNeuRise will host several online talks throughout May-June on the topic of naturalistic behavior from the following speakers: Wednesday, 5 May, 5pm CET Asaf Gal (Kronauer Lab, The Rockefeller University, USA) Daniel Knebel (Ayali Lab, Tel Aviv University, Israel) Wednesday, 19 May, 5pm CET Constanze Lenschow (Lima Lab, Champalimaud Research, Portugal) Takashi Yamaguchi (Lin Lab, NYU, USA) Wednesday, 2 June, 5pm CET Ayelet Sarel (Ulanovsky Lab, Weizmann Institute of Science, Israel) Tu Anh Nguyen Thi (el Jundi Lab, University of Wuerzburg, Germany) Wednesday, 16 June, 5pm CET Yael Bitterman (Luethi Lab, Friedrich Miescher Institute, Switzerland) Adam Calhoun (Murthy Lab, Princeton University, USA) For more information, please visit our website (https://neurise.github.io/) find us on WorldWideNeuro (https://www.world-wide.org/Neuro/WWNeuRise/) or follow us on Twitter (https://twitter.com/WWNeuRise) We are actively searching for PhD students and postdocs to give talks in our upcoming seminar blocks. On our website (https://neurise.github.io/) you can find an application form to directly apply, as well as a recommendation form, where you can suggest individuals from your lab, institute, or otherwise who you think might have an interesting story to tell! We are looking forward to seeing you at our upcoming seminars! The organising committee, Ellen Boven (Apps lab, University of Bristol) Christina Buetfering (Häusser lab, University College London) Lucie Descamps (Kentros lab, Norwegian University of Science and Technology) Gily Ginosar (Ulanovsky lab, Weizmann Institute) Loreen Hertäg (Clopath lab, Imperial College London) Joram Keijser (Sprekeler lab, TU Berlin) Bill Podlaski (Machens lab, Champalimaud Research)

April 29, 2021

Open Position for a PhD Candidate at the Donders Centre for Cognition

by Nasir Ahmad

*Dear Colleagues,* *We invite applicants for a PhD position on 'Bio-inspired learning algorithms for efficient and robust neural network models with a focus on neuromorphic computing and control of complex environments'.* https://www.ru.nl/english/working-at/vacature/details-vacature/?recid=11475… This project is embedded within the European Laboratory for Learning and Intelligent Systems (ELLIS) Unit in Radboud AI. The aim is to develop highly effective algorithms for training artificial neural network models which make use of (biologically plausible) information local to the individual nodes of the network. This locality will allow efficient implementation and testing of these algorithms on neuromorphic computing systems. The efficacy of the algorithms will be tested in the context of relevant reinforcement learning tasks using a control system theoretic approach to interaction with modelled environments. This work entails a theoretical (mathematical) development of state-of-the-art biologically plausible learning rules and reinforcement learning strategies alongside implementation/testing of these algorithms in the form of neuromorphic computing algorithms and agent-based artificial neural network modelling. We offer you a full-time (100%) position for 4 years. This project is supervised by Prof. van Gerven, Dr Nasir Ahmad and Dr. Bodo Rueckauer. You will be employed at the Artificial Intelligence department of the Donders Institute for Brain, Cognition and Behaviour, where you will have the opportunity to collaborate and interact with renowned international experts in machine learning, computational neuroscience and neuromorphic computing. You will also benefit from the extensive training programme of the Donders Graduate School. Additionally, you will have the opportunity to supervise MSc and BSc students in their thesis projects. 10% of your appointment will be devoted to support tasks in the ELLIS unit, such as helping to organise ELLIS activities or (co)supervision of ELLIS-related projects. If you are interested, please follow the link below for more information and instruction on how to apply: https://www.ru.nl/english/working-at/vacature/details-vacature/?recid=11475… The deadline is 16th May 2021. Feel free to email me or Marcel van Gerven ( marcel.vangerven(a)donders.ru.nl) with any questions/thoughts. Best wishes, Nasir Ahmad

April 29, 2021

Doctoral positions in experimental and computational neuroscience in Mainz and Frankfurt, Germany

by Matthias Kaschube

POSITIONS: The groups of Simon Rumpel at the Medical Center of the University of Mainz and Matthias Kaschube at FIAS in Frankfurt, Germany, together have openings for fully funded doctoral positions in experimental and computational neuroscience. The two groups tightly interact on several interdisciplinary joint projects funded by the German Research Foundation (DFG). Research combines behavioral learning assays, chronic imaging of synapses and activity patterns in the auditory cortex of mice, machine learning-assisted image analysis and data analysis, and neural circuit modelling. The overarching goal of these projects is to gain a deeper understanding of the neural underpinnings of adaptive, yet stable behavior by bridging studies of the dynamic connectome, large scale population activity and behavioral learning. The positions are available immediately. LAB ENVIRONMENTS: The experimental work will be carried out at the Medical Center of the Johannes Gutenberg University in Mainz offering methodology for advanced approaches in systems neuroscience including two-photon microscopy and molecular interventions using AAV vector systems (www.unimedizin-mainz.de/agrumpel) The theoretical work will be carried out primarily at FIAS, a research institution dedicated to fundamental theoretical research in various areas of science (https://www.fias.science/en/neuroscience/research-groups/matthias-kaschube/) FIAS hosts state-of-the-art facilities and has tight links to neuroscience centers at the Goethe University, the Max-Planck Institute for Brain Research and the Ernst Strüngmann Institute for Neuroscience. The Rhine-Main area including the cities of Frankfurt and Mainz is a vibrant metropolitan area in the heart of Europe and boasts a rich cultural community. Due to the strong interactive nature, mutual short- and long-term visits in both labs will be part of the project. QUALIFICATIONS: This call for applications is geared towards theoreticians as well as experimentalists, and also offers a unique opportunity to all who see themselves in between the two poles. Selection criteria include scientific enthusiasm, strong experimental or quantitative skills and past research accomplishments. Applicants must have received training and a master’s degree or equivalent in a relevant quantitative discipline including biomedicine, biology, computer science or physics. Previous experience in neurobiology is advantageous but not essential. APPLYING: Applicants should email a brief letter of intent, a detailed CV and the names of at least two scientists who can give references (in a single PDF) to Simon Rumpel (sirumpel(a)uni-mainz.de, emphasis on the experimental aspects) or Matthias Kaschube (kaschube(a)fias.uni-frankfurt.de emphasis on the computational aspects). The position is available immediately, and we look forward to reviewing applications as they arrive. Both Mainz University and FIAS are dedicated to building a diverse community in its training and employment programs.

April 29, 2021

3 days remaining to submit a "Trainee Talk" for the second Canadian Computational Neuroscience Spotlight

by Scott Rich

The second edition of the Canadian Computational Neuroscience Spotlight (CCNSv2) is fast approaching, with the meeting taking place this coming May 17-18. We now have a permanent homepage for the meeting at ccnsmeeting.ca where you can see details on our finalized list of speakers and our four fantastic session chairs: Drs. Maurizio De Pitta, Etay Hay, Carmen Canavier, and Bratislav Misic. *There are now three days remaining for trainees (undergrads, grad students, postdocs, and research scientists) to submit an abstract for a "trainee talk" via https://forms.gle/bsbrvZca6F1q62RA6 <https://forms.gle/bsbrvZca6F1q62RA6>*. We anticipate all submissions that reasonably fall under the broad banner of "computational neuroscience" will be accepted unless the demand far exceeds our expectations. Talks will either be 8 minutes (with 2 minutes for questions) or 12 minutes (with 3 minutes for questions) depending on the demand. Four submissions that are both the most meritorious and best correspond with the themes of our sessions will be offered a longer, "spotlight" presentation. Please be sure to register for the meeting itself at https://www.crowdcast.io/e/ccnsv2/register if you submit a trainee abstract. Please feel free to spread the news about our meeting to anyone who might be interested as well! We look forward to seeing you at CCNSv2. Sincerely, – Scott Rich, Ph.D. Postdoctoral Research Fellow, Krembil Research Institute – Andreea Diaconescu, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH – John Griffiths, Ph.D. Independent Scientist, Krembil Center for Neuroinformatics at CAMH – Milad Lankarany, Ph.D. Scientist, Krembil Research Institute

April 28, 2021

Open PhD Position on Machine Learning for Brain Connectivity in Clinical Neuroscience

by Emanuele Olivetti

We are pleased to announce the opening of one PhD position in neuroinformatics at the International Doctoral School in Cognitive and Brain Sciences (CIMeC) of the University of Trento, Italy. The PhD Grant is funded by the Neuroinformatics Laboratory (NILab) of Fondazione Bruno Kessler (FBK). The position is part of the “Neusurplan” project, an integrated approach to neurosurgery planning based on multimodal and longitudinal data. Neuroimaging methods, like structural, functional, and diffusion magnetic resonance imaging (MRI), can be used to investigate the anatomical and functional connectivity of the brain. In this project, the candidate will pursue research on machine learning methods for neuroimaging data analysis to study and characterize brain connectivity, with applications to longitudinal studies and clinical practice. The ideal candidate should have a mixed background in neuroimaging techniques and numerate disciplines, like computer science, engineering, physics, or mathematics. This project is in collaboration with the Division of Neurosurgery, S. Chiara Hospital, Trento (IT). The position is for a 4 year PhD program (Nov. 1, 2020- Oct. 31, 2024). Courses are in English. The salary is starting at approximately €1.200/mo., net. An additional personal budget of around €5.000 is provided for research and mobility. The University of Trento ranks among top Italian Universities ( https://www.unitn.it/en/ateneo/1636/rankings) Fondazione Bruno Kessler ranks first among the Italian research centers in Engineering and Computer Science ( https://magazine.fbk.eu/en/news/fbk-ranks-1st-in-italy-for-scientific-excel… ). Why choose Trento? ( http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento) Important dates: Deadline for application: 25 May 2021 Evaluation interview: 28 June 2021 Beginning of PhD program: 1 November 2021 Apply now: https://www.unitn.it/en/ateneo/1942/announcement-of-selection https://www.unitn.it/drcimec/105/2021-topic-specific-grants-and-descriptions You are kindly invited to contact in advance Emanuele Olivetti ( olivetti(a)fbk.eu) and Paolo Avesani (paolo.avesani(a)unitn.it) Recent related publications: - Giulia Bertò, Daniel Bullock, Pietro Astolfi, Soichi Hayashi, Luca Zigiotto, Luciano Annicchiarico, Francesco Corsini, Alessandro De Benedictis, Silvio Sarubbo, Franco Pestilli, Paolo Avesani, Emanuele Olivetti, "Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation", Neuroimage, 2021, https://doi.org/10.1016/j.neuroimage.2020.117402 - Gabriele Amorosino, Denis Peruzzo, Pietro Astolfi, Daniela Redaelli, Paolo Avesani, Filippo Arrigoni, Emanuele Olivetti, "Automatic Tissue Segmentation with Deep Learning in Patients with Congenital or Acquired Distortion of Brain Anatomy", Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology (MLCN 2020), https://doi.org/10.1007/978-3-030-66843-3_2 - Pietro Astolfi, Ruben Verhagen, Laurent Petit, Emanuele Olivetti, Jonathan Masci, Davide Boscaini, Paolo Avesani, "Tractogram filtering of anatomically non-plausible fibers with geometric deep learning", Medical Image Computing and Computer Assisted Intervention (MICCAI 2020), https://doi.org/10.1007/978-3-030-59728-3_29 -- Emanuele Olivetti, Ph.D. Senior Research Scientist at Bruno Kessler Foundation (FBK-ICT) NeuroInformatics Laboratory (NILab) http://nilab.fbk.eu Center for Mind and Brain Sciences (CIMeC), University of Trento Via delle Regole 101 - 38123 Mattarello (Trento), ITALY olivetti(a)fbk.eu - +39 0461314179 emanuele.olivetti(a)unitn.it - +39 0461282760 -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

April 28, 2021

Open positions in the Vogels Lab

by Tim Vogels

Dear Colleagues, the Vogels lab has two open postdoctoral positions. TL;DR, if you liked our last NeurIPS paper https://www.biorxiv.org/content/10.1101/2020.10.24.353409v1 <https://www.biorxiv.org/content/10.1101/2020.10.24.353409v1> and you think you can contribute and imagine, oh, the places we’ll go from here,…from one of the most liveable cities in the world, … DO apply. — We are looking for at least two scientists to join the vogelslab.org as postdocs at the @ISTAustria near Vienna. The successful candidate will join an ongoing ERC funded project to discover families of spike-induced synaptic plasticity rules by way of numerical derivation. Together, we will define and explore search spaces of biologically plausible plasticity rules expressed e.g., as polynomial expansions or multi layer perceptrons. We aim to compare the results to various experimental and theoretical data sets, including functional spiking network models, human stem-cell derived neural network cultures, in vitro and in vivo experimental data. We are looking for someone who can expand and develop our multipurpose modular library dedicated to optimization of non-differentiable systems. Due to the modularity of the library, the candidate will have extensive freedom regarding which optimization techniques to use and what to learn in which systems, but being a team player will be a crucial skill. A conceivably successful candidate will have a strong expertise in numerical simulations, and specifically spiking neuron models, and some knowledge in the field of synaptic plasticity. A strong background in applied maths, especially in numerical optimization would be desirable. Some of the questions we ponder: How to express high dimensional rules in However, we can hire more than one person, and we would also be interested in someone who can contribute to design, implementation and maintenance of a library dedicated to performing numerical optimization in non-differentiable systems on large scales. We are thinking about how to simulate spiking neural networks with complex, unsupervised and supervised plasticity rules efficiently, in parallel, on a cluster. Depending on your (flexible, possibly immediate) starting date we can offer up to 4-year contracts with competitive salaries, benefits, vacation time and ample budget for materials and travel in a tranquil and inspiring environment. The Vogelslab, and the IST Austria is located in Klosterneuburg, a historic city northwest of Vienna. The campus is located in the middle of the beautiful landscape of the Vienna Woods, 30 minutes from downtown Vienna, the capital of Austria that consistently scores in the top cities of the world for its high standard of living. If you are interested, send an email with your application to Jessica . deAntoni [at] ist.ac.at. Your application should include your CV, your most relevant publication, contact information for 2 or more references, and a cover letter with a short description of you & your career, and a brief discussion of what you think is the greatest weakness of the above mentioned NeurIPS paper (and maybe how you would go about fixing it). We are looking to build a diverse and interesting environment, so if you bring any qualities that make our lab (and computational neuroscience at large) more diverse than it is right now, please consider applying. We will begin to evaluate applications at the end of April and aim to get back to you with a decision within 5 weeks of your application. We are also looking for people with a strong background in maths and machine learning, and an intense interest in neuroscience. Specifically, we will focus on (GABAergic, <http://www.neurotheory.ox.ac.uk/~timv/pub/VogelsScience2011.pdf> codependent <http://www.neurotheory.ox.ac.uk/~timv/pub/Hennequin2017.pdf>, and machine-learning inspired <https://fzenke.net/wp-content/uploads/2018/03/ZenkeGanguli2018_SuperSpike.p…>) synaptic plasticity, and modulated <https://www.nature.com/articles/s41593-018-0276-0> neural network dynamics. <http://www.neurotheory.ox.ac.uk/~timv/pub/HennequinNeuron2014.pdf> Finally, we are keen to hear from women and members of underrepresented groups in neuroscience. Please email me with any questions or thoughts. Best wishes, Tim Vogels --- Professor Neurotheory IST Austria vogelslab.org +43 2243 9000 2170

April 27, 2021

Post-doc in the Neurophysiology of Attention & Decision Making at UCLA

by Bisley, James

Apologies for cross-posting We invite applications for a post-doc position studying the interactions of attention and decision making in parietal cortex. The work will include recording from cortical areas MT and LIP while animals perform a visual search task utilizing moving dot patterns. For more information about the sort of work done in the lab, check out our publications at https://www.ncbi.nlm.nih.gov/myncbi/james.bisley.2/bibliography/public/. Applicants should have a strong background in systems neurophysiology, behavioral training or computational neuroscience and be comfortable working independently on all aspects of the project. Previous experience with NHP recording and data analysis is desirable. Candidates should hold a PhD in neuroscience, psychology or a related discipline. The position is initially for 12 months with the possibility of renewal. Compensation will be commensurate with relevant experience. Candidates should send a CV, a brief statement of research experience and interests, expected date of availability, and the contact information for two references to James Bisley (jbisley(a)mednet.ucla.edu<mailto:jbisley@mednet.ucla.edu>). Cheers, James ________________________________ UCLA HEALTH SCIENCES IMPORTANT WARNING: This email (and any attachments) is only intended for the use of the person or entity to which it is addressed, and may contain information that is privileged and confidential. You, the recipient, are obligated to maintain it in a safe, secure and confidential manner. Unauthorized redisclosure or failure to maintain confidentiality may subject you to federal and state penalties. If you are not the intended recipient, please immediately notify us by return email, and delete this message from your computer.

April 26, 2021

Postdoc position on causal explanations in reinforcement learning at the University of Vienna

by Moritz Grosse-Wentrup

We have an opening for a postdoc position in the Research Group Neuroinformatics at the University of Vienna [1]. The position is funded by the CHIST-ERA project CausalXRL - Causal eXplanations in Reinforcement Learning [2]. The project aims to equip reinforcement learning agents with causal structure learning and reasoning abilities, enabling them to explore their environment more efficiently and justify their actions, e.g., in medical decision support. All work will be done in close collaboration with partners at the University of Sheffield and Inria Lille. The position is available for three years, with an earliest (but reasonably flexible) starting date on July 1st. Salary is according to the Collective Bargaining Agreement for university staff at the University of Vienna (job group B1 100% [3]). Our ideal candidate would have * a background in computer science or mathematics, * recently finished their Ph.D. on reinforcement learning or causality, * published first-author papers at internationally recognized machine learning conferences (e.g., NeurIPS, ICML, UAI, ECML) or in prominent journals. We will consider all applicants with a strong track record in machine learning or artificial intelligence. We strive to be a heterogeneous research team and particularly welcome applications by women, transgender and intersex candidates, people of colour, disabled applicants and candidates from other underrepresented groups. Disabled applicants will receive preference over equally qualified non-disabled applicants. Your application should include a cover letter, a CV, relevant transcripts, and contact information of at least two referees. Please submit your application documents (as one PDF file) to fsg.neuroinformatics(a)univie.ac.at. We will begin screening applications on May 17th. Applications will be considered until the position is filled. Our offices are in downtown Vienna, which has been ranked the most liveable city globally for two years in a row [4]. The University of Vienna is one of Europe's largest universities (with >90k students) and has a vibrant research community. If you have any questions before applying, please contact me at moritz.grosse-wentrup(a)univie.ac.at! 1. https://ni.cs.univie.ac.at/ 2. https://www.chistera.eu/projects/causalxrl 3. https://personalwesen.univie.ac.at/en/jobs-recruiting/job-center/salary-sch… 4. https://www.eiu.com/topic/liveability -- Univ.-Prof. Dr.-Ing. Moritz Grosse-Wentrup Research Group Neuroinformatics Faculty of Computer Science University of Vienna Hörlgasse 6, A-1090 Wien, Austria moritz.grosse-wentrup(a)univie.ac.at +43-1-4277-79610 http://neural.engineering/

April 26, 2021

FINAL call to register for neuroscience workshops!

by Mary

With just 2 weeks to go, this is the final call for participants to register for upcoming neuroscience online courses, organized by ScienceBeam Academy, as described below: 1) “Deep Dive into Event Related Potentials (ERPs) Technique” Online Course Prospective overview of the sessions: 1. Basics of EEG signal and EEG recordings ➢ Overview of the theory behind neural signals (History) ➢ Generation and Propagation of ERP and EEG ➢ Different EEG Recording Systems with its specifics (Amplifier, Electrodes etc.) ➢ 10/20 Electrode System, Reference, Montages, Impedance, etc. ➢ Brain Rhythms and Cognition (Based on Clinical and Research Studies) 2. Basics of ERP Components ➢ ERP Components (MMN, P300, N400, N170, VPP, CNV, Sensory ERP Components, etc.) ➢ Difference Wave, Forward-Inverse Problem ➢ Challenges in ERP Source Localization ➢ Peaks and Components 3. EEG-ERP Prepossessing with Various Preprocessing Pipelines ➢ Basic Principles and Challenges ➢ Filtering, Baseline Correction, Interpolation, Artifact Rejection and Correction, Re-referencing, ICA etc. ➢ Pipelines: MAKATO, HAPPE, BEAP and etc. 4. Experimental Design ➢ Principles of Experimental design for ERP in Clinical and Research Settings ➢ Significance of Measurement Window ➢ Common Design Problems and Solutions ➢ Case Studies on research articles with good and bad design 5. Basic Analysis ➢ Quantifying ERP Amplitudes and Latencies ➢ Introduction to the Analysis tool boxes (EEGLAB, ERPLAB) ➢ FFT, Time Frequency Analysis 6. Common Mistakes (in lack of parameters) ➢ Overlapping ➢ Filtering ➢ Epoching ➢ Baseline Correction ➢ Measurement Window • Instructor: Mrs. Pragati Gupta, M.Sc. in Neuro-psychology from Gujarat Forensic Sciences University, India and a Student Member at Indian Academy of Neuroscience • Course Length: 7-sessions online course • Introductory webinar: https://sciencebeam.com/erplab-webinar/ • Registration: https://sciencebeam.com/pragati-gupta-course/ o Deadline: May 5, 2021 2) “Modeling Electrophysiological Activities: From Single Neuron to Nervous Tissue” Online Course. Theoretical and experimental hands-on course including lab sessions, in which you will learn about extracellular recording from rat models and also working with single-unit and Local Field Potential (LFP) data. Prospective overview of the sessions: 1. Session 1: ➢ Systems and complex system in neurosciences ➢ Origins of electrophysiological signals and measurements ➢ Electrophysiology and relevant features for computational modeling: o Membrane potential o Raster plot o Local field potential 2. Session 2: ➢ Understanding the time evolution of the electrophysiological signals from a dynamical systems point of view. ➢ Introduction to dynamical systems for neurosciences: o Differential equations o Phase space representation o Stability and domain of attraction ➢ Unidimensional and bidimensional models o Dynamics of integrate-and-fire models o Repertoire of 2 D models o Reduction of Hodgkin-Huxley model 3. Session 3: ➢ 2D and Higher dimensions models: o Particular role of the reset o Possibility of chaos ➢ Models of synapses ➢ Limits of models: o Biophysical and mechanistic description o Phenomenology ➢ Introduction to the first lab session (with Brian2 simulator) 4. Session 4: ➢ First Lab Session: o Repertoire of electrophysiological patterns o Models of networks o Global measure on simulations 5. Session 5: ➢ Second lab session: o analysis of the results o relations to the data ➢ Conclusive discussion • Instructor: Dr. Damien Depannmaecker, Post-Doc researcher at Department of Integrative and Computational Neuroscience, Paris Saclay Institute of Neuroscience, France • Course Length: 5-sessions hands-on online course • Introductory webinar: https://sciencebeam.com/modeling-electrophysiological-activities/ • Registration: https://sciencebeam.com/online-course-modeling-electrophysiological-activit… o Deadline: May 20, 2021 If you require any further information, feel free to contact us: workshop(a)sciencebeam.com

April 26, 2021