- Comp-neuro - lists.cnsorg.org

Advanced Electrophysiology Post-doc Position Available - Interventional Psychiatry Program, Minneapolis, MN, USA
by Hiba Sheheitli 01 Aug '23

01 Aug '23

*About the Job* Dr. Ziad Nahas (Interventional Psychiatry Lab) in the University of Minnesota Department of Psychiatry and Behavioral Sciences is seeking an outstanding candidate for a postdoctoral position to conduct and analyze the effects of neuromodulation on brain activity in mood disorders. Candidates should be passionate about advancing knowledge in the area of translational research of depressive disorders and other mental health conditions with a focus on invasive and non-invasive brain stimulation treatments. The position is available June 1, 2023, and funding is available for at least two years. *Qualifications* Required Qualifications: ●PhD in relevant field (neuroscience, psychology, cognitive science) ●Strong programming and/or data analysis skills. MATLAB or Python is essential. C/C++ (and derivatives), LabVIEW, and scripting languages could be useful. Prior experience with data acquisition hardware including behavioral as well as EEG would be helpful. Proficiency with Microsoft Office software ●Experience with neurophysiology (human or animal), psychophysics and/or brain stimulation is ideal. ●Excellent verbal and written communication skills, with specific documentation of those skills through published work and oral scientific presentations. ●Demonstrated ability to work independently and to independently overcome complex technical challenges. ●Interpersonal skills appropriate for collaboration in a very multidisciplinary and highly diverse environment. Preferred Qualifications: •Previous experience with psychiatric patient populations, the biological mechanisms of mental illness, and/or medical device development. •Signal processing and/or computer science background. •Previous experience with human functional imaging or electrophysiology. *About the Department* Dr. Ziad Nahas’s Lab is located primarily at the Interventional Psychiatry Program’s St. Louis Park clinic, with additional study activity at UMN and M Health Fairview sites on the UMN campus. Our work focuses on advancing translational research of mood dysregulation and depressive disorders. Specific interests and areas of expertise include: ● Improving patient care of treatment resistant disorders using neuromodulation techniques. ● Functional neuroimaging (fMRI), electroencephalography (EEG) and brain stimulation modalities: Transcranial magnetic stimulation (TMS), transcranial alternating current stimulation (tACS), vagus nerve stimulation (VNS), prefrontal cortical stimulation (PCS), deep brain stimulation (DBS), electroconvulsive therapy (ECT) and focal electrically administered seizure therapy (FEAST). ● Increasing equitable access to neuromodulation interventions for patient care. To learn more about Dr Ziad Nahas and the Department of Psychiatry & Behavioral Sciences, please visit: https://med.umn.edu/bio/psychiatry/ziad-nahas *Apply here: * https://hr.umn.edu/Jobs/Find-Job <https://hr.umn.edu/Jobs/Find-Job> (Click on External Candidates and search for 355003 to find the Job Posting)

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NeurIPS Workshop "Information-Theoretic Principles in Cognitive Systems"
by Rava A. da Silveira 30 Jul '23

30 Jul '23

NeurIPS Workshop: "Information-Theoretic Principles in Cognitive Systems" CALL FOR PAPERS Website (with submission information): https://sites.google.com/view/infocog-neurips-2023/call-for-papers Contact: infocog.neurips2023(a)gmail.com Important Dates: * Paper submission deadline: September 20, 2023 * Author notification: October 27, 2023 * Camera ready deadline: November 27, 2023 The second InfoCog@NeurIPS workshop aims to further the understanding of information flow in cognitive processes and neural networks models of cognition by bringing together researchers from multiple disciplines, including machine learning, cognitive science, neuroscience, and information theory. This is the second workshop of this kind in NeurIPS. This year the workshop will continue last year’s community-building momentum and will additionally focus on advancing two main goals: First, providing a fruitful platform for discussing formulations of storage and processing of information in human and artificial cognitive systems, via information-theoretic measures. Specifically, we aim to further integrate information theory researchers in such discussions, deepening the mathematical knowledge and tools shared across disciplines. [NZ1] Second, facilitating research on addressing the challenges of computing information theoretic quantities, specifically for the needs of cognitive science and machine learning. We invite short submissions (up to 4 pages – NeurIPS format) that present original work related to information theory and cognitive systems, and particularly encourage submissions of collaborative interdisciplinary work. Examples of specific topics of interest include but are not limited to: * Novel information-theoretic approaches to cognitive functions (e.g., perception, decision making, language, social reasoning, etc.) * Method and approaches for the validation of information theoretic formalisms in human and artificial cognition * Novel methods and approaches for the computation and/or estimation of information theoretic quantities and their applications to human and artificial cognition * Challenges and limitations of the use of information theory in studying cognitive systems * Application of information theory to training human-aligned artificial agents, i.e., agents that can better communicate and cooperate with humans All accepted papers will be presented in a poster session during the workshop, and a number of papers will also be selected for an oral presentation. We expect to have limited resources to offer financial aid to selected participants. More details will follow upon acceptance.

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Postdoc in computational modeling at Stanford Cognitive & Systems Neuroscience Lab
by Mai-Phuong K Bo 27 Jul '23

27 Jul '23

The Stanford Cognitive and Systems Neuroscience Laboratory (scsnl.stanford.edu) invites applications for a postdoctoral fellowship in human brain network analysis and modeling. We seek candidates with strong research backgrounds in one or more of the following areas: resting-state and task-evoked fMRI connectivity, structural HARDI-based connectivity, neurophysiological modeling of brain networks, Bayesian modeling, machine learning, and deep neural networks. Candidates must have strong computational skills and a PhD in computational neuroscience, computer science, physics, biomedical engineering or related fields. This is an exciting opportunity to work on multiple NIH- and Stanford-funded projects using multimodal (fMRI, optogenetic, DTI, EEG) brain imaging techniques in multiple clinical populations and normative groups. The successful candidate will develop a vigorous research program that contributes to, and complements, ongoing research studies. The candidate will have access to state-of-the-art brain imaging and HPC/GPU facilities.  Please email a CV, statement of research interests and relevant background, and have three letters of reference sent to Prof. Vinod Menon at  scsnl.stanford+postdoc(a)gmail.com<mailto:scsnl.stanford@gmail.com> Mai-Phuong Bo (She/Her) Lab & Recruitment Manager Stanford Cognitive & Systems Neuroscience Lab Department of Psychiatry & Behavioral Sciences Email: maipbo(a)stanford.edu [cid:93b74359-266e-493c-9def-d9fb37f515df]

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PhD position at the TU Delft at the crossroads of machine learning and hardware design
by justin＠dauwels.com 27 Jul '23

27 Jul '23

Dear colleagues, We are looking for a highly motivated Ph.D. candidate with a background in machine learning and/or in electrical engineering for a project at the TU Delft at the crossroads of machine learning and hardware design. Building autonomous agents that can reliably compute and take decisions in noisy and uncontrolled environments is among the top research areas in today's artificial intelligence (AI). Yet, doing so within constrained power budgets for battery-operated edge devices is currently an open challenge. Indeed, while current cutting-edge deep-learning approaches can now reach acceptable performance in such environments, they are still subject to adversarial attacks and need a backend of GPU clusters, thereby requiring 4 to 6 orders of magnitude more power than is allowed for by the edge power budgets. On both ends of the spectrum of learning algorithms are the error backpropagation algorithm, i.e. the workhorse of modern deep learning, and local Hebbian learning rules, which are inspired by the brain's synaptic plasticity mechanisms. The former offers excellent performance but its energy/memory footprint is incompatible with low-power edge devices, while the latter allows for low-cost hardware implementations but can hardly be deployed beyond toy problems. In this PhD project, you will tackle this challenge by: * developing a theoretical framework that will allow exploring and generating, in a use-case-driven fashion, emerging learning algorithms that combine the strengths of local brain-inspired learning and backprop, * with a hardware/algorithm co-design approach, developing custom neuromorphic silicon prototypes (digital, then mixed-signal) for the proposed learning rules * investigating the deployment of these adaptive prototypes in resource-constrained use cases at the edge, such as brain implants for seizure detection. This project is a collaboration between Dr. Charlotte Frenkel (neuromorphic hardware, hardware/algorithm co-design, brain-inspired machine learning) and Dr. Justin Dauwels (Bayesian machine learning, computational neuroscience, biosignal processing). About the Department of Microelectronics at TU Delft: https://microelectronics.tudelft.nl/ About the CogSys research lab: https://ei.et.tudelft.nl/Research/theme.php?id=63 The expected starting date is 01/11/2023 and deadline for application is 01/09/2023. For more information and to apply, please visit this website <https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details? jobId=13043&jobTitle=PhD%20Position%20in%20Bio-plausible%20Local%20Learning% 20Rules%20for%20Adaptive%20Neuromorphic%20Hardware> . Greetings, Justin. _______________________________________________________________ Justin Dauwels j.h.g.dauwels(a)tudelft.nl <mailto:j.h.g.dauwels@tudelft.nl> Associate Professor http://cas.tudelft.nl/ Fac. EEMCS Section Circuits and Systems Mekelweg 4 2628 CD Delft, The Netherlands _____________________________________________________________________

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SUBMIT YOUR WORK TO COMPLEX NETWORKS 2023 BEFORE SEPT. 02, 2023
by Hocine Cherifi 26 Jul '23

26 Jul '23

*12* *th **International Conference on Complex Networks & Their Applications* Menton Riviera <https://www.menton-riviera-merveilles.co.uk/>, France November 28 - 30, 2023 COMPLEX NETWORKS 2023 <https://complexnetworks.org/> You are cordially invited to submit your contribution until *September 02, 2023*. *SPEAKERS* · Michael Bronstein <https://www.cs.ox.ac.uk/people/michael.bronstein/> University of Oxford UK · Kathleen Carley <https://www.cylab.cmu.edu/directory/bios/carley-kathleen.html> Carnegie Mellon University USA · Manlio De Domenico <https://manliodedomenico.com/> University of Padua Italy · Danai Koutra <http://web.eecs.umich.edu/~dkoutra/> University of Michigan USA · Romualdo Pastor-Satorras <http://www.fen.upc.edu/~romu/> Univ. Politècnica de Catalunya Spain · Tao Zhou <https://scholar.google.com/citations?user=MXgWgmEAAAAJ&hl=en> USTC China *TUTORIALS* · Tiago de Paula Peixoto <https://skewed.de/tiago> CEU Vienna Austria · Maria Liakata <https://www.turing.ac.uk/people/researchers/maria-liakata> Queen Mary University of London UK *PUBLICATION* Full papers (not previously published up to 12 pages) and Extended Abstracts (about published or unpublished research up to 4 pages) are welcome. · *Papers *will be included in the conference *proceedings edited by Springer* · *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* Extended versions will be invited for publication in *special issues of international journals:* o Applied Network Science <https://appliednetsci.springeropen.com/> edited by Springer o Advances in Complex Systems <https://www.worldscientific.com/toc/acs/24/02> edited by World Scientific o Complex Systems <https://www.complex-systems.com/about/> o Entropy <https://www.mdpi.com/journal/entropy> edited by MDPI o PLOS <https://journals.plos.org/plosone/> one <https://journals.plos.org/plosone/> o Social Network Analysis and Mining <https://link.springer.com/journal/13278> edited by Springer *SUBMISSION* https://complexnetworks.org/submission/ *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Epidemics o Community Structure o Motifs o Network Mining o Network embedding o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Controllability o Synchronization o Visual Representation o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems o Financial and Economic Networks o Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics o Earth Sciences Applications o Resilience and Robustness of Complex Networks o Networks for Physical Infrastructures o Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks o Graph-Based Natural Language Processing *GENERAL CHAIRS* Hocine Cherifi (University of Burgundy, France) Luis M. Rocha (Binghamton University, USA) Join us at COMPLEX NETWORKS 2023 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Applied Network Science <https://appliednetsci.springeropen.com/> Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

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Call for Abstract Submission FRoBio: Freiburg Robotics and Biology Conference
by Timo Oess 24 Jul '23

24 Jul '23

Dear all, We are pleased to announce the FRoBio: Freiburg Robotics and Biology Conference - Bringing together nature and technology. The conference will take place on 22nd of November until 24th of November 2023 at the University of Freiburg, Germany. The event brings together international experts of different disciplines, such as biology, chemistry, medicine, materials science, nanotechnology, electrical engineering, mechanical engineering, optics, and robotics to share so far untackled research questions or current challenges, novel methods and approaches that are applicable for multiple fields or interdisciplinary research. Abstract submission is now open for in-person participants and the deadline is September, 8th 2023. The registration for online participants will be open in October 2023. For further information on the conference and In-Person / Online Registration please visit the conference website. <https://www.frias.uni-freiburg.de/de/veranstaltungen/nachwuchskonferenzen/F…> We are looking forward to seeing you at FRoBio in November 2023! Best regards, The Organizing Committee

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Apply to the Allen Institute's OpenScope program
by Anton Arkhipov 24 Jul '23

24 Jul '23

Dear Colleagues, Applications are now accepted for the Allen Institute's OpenScope program. Please apply! The OpenScope program, supported by the NIH BRAIN grant U24NS113646, provides the neuroscience community access to the Allen Brain Observatories. The program was inspired by astronomical observatories, which allow a community of scientists to access platforms too large or expensive for most laboratories. Through OpenScope, anyone can propose experiments for Allen Institute staff to run on Allen Institute pipelines. If selected, the proposed experiments are performed with the Allen Institute's verified, reproducible, and open protocols for cutting-edge behavioral training, in vivo Neuropixels electrophysiology, or two-photon calcium imaging. Data produced from the experiments is then shared with applicants, and, eventually, the broader community. How to apply? The program uses a double-blinded proposal review. Individuals or teams draft and submit a proposal, with an applicant commitment to perform data analysis and pursue publication. * RFP released July 10, 2023 * 2pg Letter of Intent Due: September 12th 2023 * 6pg Full Proposal Due: November 7th 2023 * For more details: https://alleninstitute.org/division/mindscope/openscope/ * If any questions or to discuss projects, please reach out to openscope(a)alleninstitute.org<mailto:openscope@alleninstitute.org> New for 2023: Community Proposal Research Questions and Experimental Methods are proposed and voted on by the community in an open, collaborative process. The resulting data is immediately available to the community for anyone to analyze and publish. * Posted on Allen Brain Map Community Forum: https://community.brain-map.org/ * Opportunity announced in June 2023 * Research Question Phase: June-July 2023 * Methods & Analysis Phase: July-September 2023 * Final Vote by the community in November 2023 during SFN Best wishes, Anton. Anton Arkhipov Investigator Allen Institute, Seattle, WA

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ICANN 2023 - Call for Participation
by Sebastian Otte 24 Jul '23

24 Jul '23

32nd International Conference on Artificial Neural Networks ICANN 2023 https://e-nns.org/icann2023 !!! EARLY BIRD REGISTRATION ENDS ON JULY 25 !!! Conference Dates: 26th to 29th of September 2023 ======================================================================= The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2023 the School of Engineering of Democritus University of Thrace, Greece, will organize ICANN 2023. This will be held at Astoria Capsis Hotel at Heraklion city, Crete, Greece from 26th to 29th of September 2023. The conference will be organized as a HYBRID event. CONFERENCE TOPICS ICANN 2023 is a conference featuring tracks in Brain Inspired Computing, Machine Learning, and Artificial Neural Networks, with strong cross-disciplinary interactions and applications. A non-exhaustive list of topics includes: Machine Learning: Deep Learning, Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information Theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models, Recurrent Networks, Ethics of AI Brain Inspired Computing: Cognitive Models, Computational Neuroscience, Self-Organization, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Cognitive Neuroscience, Brain Informatics, Perception and Action, Spiking Neural Networks Neural Applications for: Bioinformatics, Biomedicine, Intelligent Robotics, Neurorobotics, Language Processing, Speech Processing, Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neuromorphic Computing and Edge AI, Evolutionary Neural Networks SPECIAL SESSIONS ICANN 2023 will host three special sessions: - Neurorobotics (track NRR 2023) - Recent Advances in Spiking Neural Networks (track ARNN 2023) - The challenge of errors, stability, robustness, and accuracy in deep neural networks (track ESRA in DNN 2023) BEST PAPER AWARDS ENNS will sponsor a maximum of four best paper awards. All awards will be presented during the final ceremony. TRAVEL GRANTS The European Neural Network Society sponsors a number of Student Travel Grants covering part of the costs for attending ICANN. Details are provided on the conference website. ORGANIZATION General Chairs Iliadis Lazaros, Democritus University of Thrace, Greece Plamen Angelov, Lancaster University, UK Program Chairs Antonios Papaleonidas, Democritus University of Thrace, Greece Elias Pimenidis, UWE Bristol, UK Chrisina Jayne, Teesside University, UK Honorary Chairs Stefan Wermter, University of Hamburg, Germany Vera Kurkova, Czech Academy of Sciences, Czech Republic Nikola Kasabov, Auckland University of Technology, New Zealand Organizing Chairs Antonios Papaleonidas, Democritus University of Thrace, Greece Anastasios Panagiotis Psathas, Democritus University of Thrace, Greece George Magoulas, University of London, Birkbeck College, UK Haralambos Mouratidis, University of Essex, UK Award Chairs Stefan Wermter, University of Hamburg, Germany Chukiong Loo, University of Malaysia, Malaysia Communication Chairs Sebastian Otte, University of Tübingen, Germany Anastasios Panagiotis Psathas, Democritus University of Thrace, Greece

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Mathematical Bridges for the Brain: Krembil Computational Neuroscience Symposium (October 2--3, 2023; Toronto, Canada)
by De Pitta, Maurizio 24 Jul '23

24 Jul '23

Dear colleagues, Please mark your calendars for this fall's Krembil Computational Neuroscience Hub Symposium on "Mathematical Bridges for the Brain: Theory and Practice in Neural Health and Disease," which will happen on October 2--3, 2023, hosted by the Krembil Research Center in Toronto, Canada. The Symposium has been thoughtfully crafted to showcase cutting-edge computational approaches that bridge across various brain scales, ranging from cellular to systems neuroscience, with a particular focus on translational and clinical applications. By bringing together prominent experts from the intersection of mathematics, engineering, clinical, and experimental neurosciences, we aim to delve into the depths of the latest computational methods in understanding brain pathophysiology. Speakers include: Emery Brown (Harvard/MIT) Maurizio De Pitta (Krembil / Basque Center for Applied Mathematics) Brent Doiron (UChicago) Salvador Dura-Bernal (SUNY) Lorraine Kalia (Krembil, UHN) Rahul Krishnan (UToronto) Milad Lankarany (Krembil/UToronto) Jérémie Lefebvre (UOttawa/Krembil) Wilten Nicola (UCalgary) Annabelle Singer (Georgia Tech/Emory) In keeping with the long-standing tradition of the KCNhub, the Symposium is not just a platform for academic exchange; it also presents a wonderful opportunity for networking and forging connections with fellow computational neuroscientists and digital medicine enthusiasts Please visit the Eventbrite site for further details on the program and registration https://www.eventbrite.ca/e/krembil-computational-neuroscience-kcn-symposiu… Due to the limited number of seats available, registration is free but mandatory. Looking forward to seeing you in Toronto this fall. On behalf of the Organizing Committee. Maurizio De Pitta ----- Maurizio DE PITTA Principal Investigator Neuron-Glia Interactions Lab (NGILab) Krembil Research Institute, 4KD-509 60 Leonard Ave, Toronto, ON M5T 0S8, CA +1.416.603.5800 ext. 3290 This e-mail may contain confidential and/or privileged information for the sole use of the intended recipient. Any review or distribution by anyone other than the person for whom it was originally intended is strictly prohibited. If you have received this e-mail in error, please contact the sender and delete all copies. Opinions, conclusions or other information contained in this e-mail may not be that of the organization. If you feel you have received an email from UHN of a commercial nature and would like to be removed from the sender's mailing list please do one of the following: (1) Follow any unsubscribe process the sender has included in their email (2) Where no unsubscribe process has been included, reply to the sender and type "unsubscribe" in the subject line. If you require additional information please go to our UHN Newsletters and Mailing Lists page. Please note that we are unable to automatically unsubscribe individuals from all UHN mailing lists. Patient Consent for Email: UHN patients may provide their consent to communicate with UHN about their care using email. All electronic communication carries some risk. Please visit the UHN website and search “Using email to Communicate with Your UHN Health Care Team” to learn about the risks of electronic communication and how to protect your privacy. You may withdraw your consent to receive emails from UHN at any time. Please contact your care provider, if you do not wish to receive emails from UHN.

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Neuronal data scientist position
by Nikolas Karalis 23 Jul '23

23 Jul '23

If you are a data scientist, programmer, or engineer, with a keen interest in helping to understand the brain, consider joining our team Neuronal Circuits & Brain Dynamics <http://neuronaldynamics.eu/> at the Paris Brain Institute <https://institutducerveau-icm.org/en/> (ICM). We study the principles of neuronal circuit organization and brain dynamics. Our work focuses on unraveling the fascinating mysteries of how the brain generates internal states and how neuromodulators, such as dopamine and serotonin, influence neuronal activity and communication between brain regions during behavior. To achieve our goals, we perform large-scale recordings from thousands of neurons simultaneously using multimodal recordings, including electrophysiological or optical imaging approaches. We employ state-of-the-art techniques, including behavioral, optogenetic, imaging, electrophysiological, and genetic approaches in mice to record and manipulate the brain activity during behavior. Using this unprecedented data, we will be able to understand information flow in the brain in ways that would be unimaginable only a few years ago. However, the scale and complexity of this data provide major challenges and unique opportunities. We are looking for computationally-orientated researchers to join our team as temporary or permanent staff members, to help us develop methods to interact and analyze our multi-dimensional neurophysiological and behavioral data, and to develop innovative analysis approaches and efficient processing pipelines, to accelerate the progress of our research on our path to understanding the brain. As a data analyst in our group, you will interact closely with experimentalists and contribute crucially to the research. Our team values diversity and welcomes researchers from all backgrounds and profiles. If your profile aligns with our research needs, we encourage you to get in touch with us. Profile - Outstanding analytical and quantitative skills - Interest in neuronal dynamics and computation, behavior, and neural circuits - Ability to analyze multi-dimensional and multi-modal data - PhD or MSc in neuroscience, data science, computer science, applied mathematics, physics, or equivalent combination of degree and experience - Experience with computational statistics, data modeling and analysis, signal processing, and modern machine-learning methods - Solid programming skills and ability to write high-quality, reusable code in Python or Matlab - Experience with software development (e.g., version control, unit testing, databases) is preferable Main responsibilities - Organize data management pipeline - Analyze neurophysiological and behavioral data - Develop analysis methods and software tools to facilitate the analysis of multi-modal and multi-dimensional neurophysiological data - Implement cutting-edge data science approaches (statistical, computational, and ML) for complex neuroscience problems - Create robust and efficient data pipelines to extract, transform, and visualize data - Develop, test, and implement scientific software (e.g., for reproducible analysis pipelines and data storage) - Interact with experimentalists to design experiments and implement analyses - Analyze current technologies, algorithms, models, and methods - As part of your role, you will have the opportunity to collaborate with other teams, attend trainings, mentor students, have independent projects, and present at major relevant conferences (Cosyne, NeurIPS) *We offer* competitive compensation and benefits within an interactive, interdisciplinary working environment, where cutting-edge science thrives and a dynamic, international research community awaits. If you would like to know more, visit our website: neuronaldynamics.eu and read about our team's mission and values <https://www.neuronaldynamics.eu/team/mission-values>. *Why join our team* - We are a young and vibrant group of scientists, fueled by curiosity and passion for understanding the brain. We work as a team and use or invent cutting-edge neurotechnologies to answer fundamental questions in neuroscience. - Our team is committed to the training, mentorship, and career development of the next generation of neuroscientists. To achieve that, we foster an inclusive and supportive environment, where we can learn and advance science while having fun in the process. - Our work is multi-disciplinary, and so is our team. Irrespective of your background and project, our research environment will expose you to a diverse range of experimental and computational aspects of systems and circuits neuroscience. We thus encourage everyone to apply, especially those from underrepresented minorities. - Working in our team will provide you with invaluable experience across all stages of research, as well as publishing and communicating research results. - Our team is affiliated with Inserm <https://www.inserm.fr/> and is located in the Paris Brain Institute (ICM) <https://institutducerveau-icm.org/>. - Our vibrant community at the ICM and throughout Paris promotes broad collaboration and learning opportunities. *How to apply* If you are eager to join our vibrant research community and contribute to groundbreaking discoveries, we warmly welcome your application. The position is available immediately, with the potential for a permanent contract based on performance. Please send a statement of your past work and future research interests, your CV, and contact information for 1-3 references to the address: contact(a)neuronaldynamics.eu -- Nikolas Karalis Neuronal Circuits & Brain Dynamics Lab <http://neuronaldynamics.eu/> - Paris Brain Institute

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