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2-year postdoc at Neurospin/INM, Paris: Computational and high field MRI characterization of learning and decision-making - Supervisor: Dr Florent Meyniel
by Zeineb Amor July 16, 2026

July 16, 2026

Dear all, A two-year postdoctoral position is available at NeuroSpin/INM (Paris, France) under the supervision of Dr. Florent Meyniel. https://computationalbrainteam.com/en/recruitment/2-year-postdoctoral-posti… *Project* Computational and high field MRI characterization of learning and decision-making *Supervisor and contact* Dr Florent MEYNIEL https://www.unicog.org/lab/the-computational-brain/ *Duration and Dates* * Initial duration: two years * Extension possible * Full-time post * Preferred starting date: October 2026 to January 2027 *Project description* Learning and decision making are intertwined processes in many everyday situations. One example is when you decide where to have lunch: should you go to the nearby coffee shop or to the university cafeteria? Learning depends on choice, because you can learn which option you prefer by trying each option repeatedly, and decision making depends on learning, because you eventually want to select the option you have learned you like best. Uncertainty plays a key role in both learning1–4 and decision making5, especially when the environment is not stationary (e.g., a new brand now runs the nearby coffee shop and you like it less). In the ANR/CEA-funded BrainSync collaborative project, we are interested in characterizing the neural representations of uncertainty6–8 and value that emerge from learning and guide decisions. Our approach combines deep phenotyping approach and multimodal imaging in the EXPLORE task5. We collected data from 16 participants who participated in one behavioral session, two 7T fMRI sessions, and two MEG sessions. 56 other participants participated in one pupillometry session and one 3T fMRI session. We also plan to record a dataset on our 11.7T MRI, and we have started to collect intracranial EEG data. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD student is working on the behavioral and 11.7T data (to be collected). We are looking for another postdoc for the already collected fMRI datasets. The postdocs and PhD student will work together to perform analyses informed by all datasets. *Profile* Ph.D. in neuroscience, machine learning or psychology, with strong programming skills, ideally in Python. Previous experience with ideally fMRI, computational modeling. You will be responsible for analyzing fMRI data and disseminating results in internal seminars, international conferences and journal articles. The working language of the lab is English. French is not required. *Workplace and environment* Dr Florent MEYNIEL leads the Computational Brain team (more info here), which is located in two places. * Institute of NeuroModulation (INM), Sainte Anne Hospital, Paris, France. The INM is part of the GHU Paris, Psychiatry & Neurosciences. The INM combines clinical activities and innovative clinical research in psychiatry with basic research in computational neuroscience. Team members spend most of their days here. * NeuroSpin, Paris-Saclay Campus, France. NeuroSpin is part of the CEA (Commissariat à l'Energie Atomique). Directed by Prof. Stanislas DEHAENE, NeuroSpin is a world-class brain imaging center equipped with a MEG system (Elekta, Neuromag) and several human MRI scanners (3T Prisma, 7T and 11.7T), all for research purposes only. The community at NeuroSpin is very scientifically stimulating, combining MRI physicists, machine learning experts, and cognitive neuroscientists. Team members go there to collect data and collaborate with their colleagues in the Cognitive NeuroImaging Unit. *Application procedure* Please send an email to Florent Meyniel (florent.meyniel(a)cea.fr) * Your CV * a research statement describing your research interests and proposed directions * the contact details of two referees Applications will be considered on a rolling basis (positions will remain open until filled). *Salary * Will follow INM standards and depend on experience. *References* 1. Meyniel, F., Schlunegger, D. & Dehaene, S. The Sense of Confidence during Probabilistic Learning: A Normative Account. PLoS Comput Biol 11, e1004305 (2015). 2. Meyniel, F., Sigman, M. & Mainen, Z. F. Confidence as Bayesian Probability: From Neural Origins to Behavior. Neuron 88, 78–92 (2015). 3. Foucault, C. & Meyniel, F. Two Determinants of Dynamic Adaptive Learning for Magnitudes and Probabilities. Open Mind 8, 615–638 (2024). 4. Meyniel, F. Brain dynamics for confidence-weighted learning. PLOS Comput. Biol. 16, e1007935 (2020). 5. Paunov, A. et al. Multiple and subject-specific roles of uncertainty in reward-guided decision-making. 2024.03.27.587016 Preprint at https://doi.org/10.1101/2024.03.27.587016 (2024). 6. Walker, E. Y. et al. Studying the neural representations of uncertainty. Nat. Neurosci. 1–11 (2023) doi:10.1038/s41593-023-01444-y. 7. Bounmy, T., Eger, E. & Meyniel, F. A characterization of the neural representation of confidence during probabilistic learning. NeuroImage 268, 119849 (2023). 8. Meyniel, F. & Dehaene, S. Brain networks for confidence weighting and hierarchical inference during probabilistic learning. Proc. Natl. Acad. Sci. 201615773 (2017) doi:10.1073/pnas.1615773114. Best regards, Zaineb Amor, PhD Research Engineer GHU Paris, Psychiatrie et Neurosciences Institut de Neuromodulation Paris, France

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Call for Extended Abstracts – WWIN 2026 Workshop @ SAB 2026
by Yoshida Naoto July 16, 2026

July 16, 2026

(Apologies for cross-posting.) Dear colleagues, We are pleased to announce that the first international workshop “Wanting What is Needed: From Homeostatic Control to Adaptive Behavior” will be held on October 19th in Berlin, Germany, as part of SAB 2026. Workshop website: https://wwin-workshop.github.io/sab2026 ====================================== Aims of the workshop ====================================== Classical reinforcement learning and cognitive models often begin with externally specified rewards. Biological organisms, by contrast, are autonomous learning agents whose behavior is constrained by the need to sustain their own viability. This workshop asks how internal physiological regulation can ground decision-making, value formation and motivated behavior. We aim to foster a shared interdisciplinary conversation across machine learning, artificial intelligence, robotics, neuroscience, biology, physiology, ethology and control theory. The goal is to clarify how homeostatic and allostatic regulation can contribute to adaptive behavior in both biological organisms and artificial agents. ====================================== Invited speakers ====================================== * Lilian A. Weber (Osnabrück University) * Lola Cañamero (CY Cergy Paris University) * Antonio Damasio (University of Southern California, online) ====================================== Extended abstracts for lightning talks and posters ====================================== * Extended abstracts of up to 3 pages (main text) * References, appendices, and acknowledgements are not included in this limit * Springer LNCS style (template available on the workshop website) Keywords: Homeostasis, Allostasis, Intrinsic needs, Value formation, Motivated behavior, Embodied robotics, Adaptive agents, Control theory, Interoception, Internal states ====================================== Important dates ====================================== * Extended Abstract Submission Deadline: August 5, 2026 * Notification of Acceptance: August 19, 2026 * Workshop Date: October 19, 2026 (afternoon) Best regards, Naoto Yoshida (Kyoto University) On behalf of the organizing committee: Boris Gutkin (École Normale Supérieure) Henning Sprekeler (Technical University of Berlin) Louis L’Haridon (ENSEA / CNRS) Lola Cañamero (CY Cergy Paris University) Ismael T. Freire (Sorbonne University) Mehdi Khamassi (Sorbonne University) --- Naoto Yoshida, PhD Program-Specific Researcher (Symbol Emergence Systems for Qualia Structures) Symbol Emergence Systems Lab. Graduate School of Informatics Research Bldg. 7 Kyoto University Yoshida-Honmachi, Sakyou-Ku, Kyoto, Japan. yoshida.naoto.8x(a)kyoto-u.ac.jp <mailto:yoshida.naoto.8x@kyoto-u.ac.jp> X: @movingsloth webpage: https://sites.google.com/view/movingsloth

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Multiple PhD positions in Cognitive Neuroscience at SISSA - application deadline 20 August 2026
by Eugenio Piasini July 15, 2026

July 15, 2026

Up to 3 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2026. SISSA is an elite postgraduate research institution for Maths, Physics and Neuroscience, located in Trieste, Italy. SISSA operates in English, and its faculty and student community is diverse and strongly international. The Cognitive Neuroscience group (https://phdcns.sissa.it/) hosts 7 research labs that study the neuronal bases of time and magnitude processing, neuronal foundations of perceptual experience and learning in various sensory modalities, motivation and intelligence, language, and neural computation. Our research is highly interdisciplinary; our approaches include behavioral, psychophysics, and neurophysiological experiments with humans and animals, as well as computational, statistical and mathematical models. Students from a broad range of backgrounds (physics, maths, medicine, psychology, biology) are encouraged to apply. The selection procedure is now open; please apply here<https://pica.cineca.it/sissa/phd-cns-02-2026/>. The application deadline for the spring admission round is 20 August 2026 at 1pm CET. For more information on the procedure, see our admissions page<https://phdcns.sissa.it/admission-procedure>. Please contact the PhD Coordinator Mathew Diamond (diamond(a)sissa.it) and/or your prospective supervisor for more information and informal inquiries.

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Faculty positions in computational/theoretical neuroscience and NeuroAI at OIST, Japan
by Erik De Schutter July 15, 2026

July 15, 2026

The Okinawa Institute of Science and Technology (https://www.oist.jp/) is an international, interdisciplinary graduate university in Japan, operating entirely in English and committed to empowering world-class researchers with the freedom, resources, and support they need to drive transformational discoveries. We are seeking outstanding scientists to join our community as tenure-track faculty members, as part of an expansion in two broad areas. We aim to appoint two tenure-track assistant professors in: * Life Sciences & Neuroscience: including theoretical and AI approaches We provide: * Core research funding for your scientific vision * Fully funded PhD students, postdoctoral researchers, lab technicians, and staff scientists * World-class core facilities and support staff * Opportunities for amplifying your scientific impact (e.g., technology transfer, outreach, collaborations, etc.) * Full administrative support and assistance with living and working in Okinawa * Competitive compensation package, including housing and commuting allowances, relocation support, family benefits, and dual-career opportunities Our culture and environment: * No faculty hierarchies or departments * A thriving international research community representing 73 countries and territories * A vibrant, safe, multicultural setting on the beautiful island of Okinawa OUR SCIENTIFIC VISION OIST empowers faculty to pursue fundamental, curiosity-driven research while encouraging connections across disciplines. Our faculty publish in top-tier journals, lead international collaborations, and attract prestigious fellowships. We support researchers not only as scientists but also as mentors, leaders, and innovators. To promote scientific excellence through a diverse and inclusive community, OIST actively encourages applications from women and other underrepresented groups. We provide a family-friendly working environment, including a bilingual child development center on campus. APPLY * Life Sciences & Neuroscience https://apply.interfolio.com/188856

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Graduate student / Postdoc position
by Goodhill, Geoffrey July 13, 2026

July 13, 2026

The emergence of spontaneous activity during cortical development Labs of Geoff Goodhill and Linda Richards Washington University School of Medicine, St Louis We are looking for a Postdoc or Graduate student to analyze and model the emergence of early patterns of spontaneous neural activity in developing cortex. We are interested in questions such as whether functionally distinct areas show common or distinct initial activity patterns, and how these patterns relate to subsequent function. This project is based on data from the dunnart (an Australian marsupial), an animal model which offers unique advantages over rodents for studying early activity since dunnarts are born at a much earlier stage of brain development. Our initial work on this project is described in https://www.pnas.org/doi/10.1073/pnas.2208654120. We are now using 2-photon imaging of soma-targeted GCaMP8m which offers data with much higher resolution and detail. The postdoc/student will work between the Goodhill and Richards labs, which are both located in a new 60,000 m^2 building dedicated entirely to neuroscience research which opened in 2023. USNews currently ranks Washington University =6th in the world for Neuroscience and Behavior. Applicants should have a strong math/engineering background and an interest in neuroscience, particularly spontaneous activity and the developing brain. To apply send a detailed CV including names of at least 3 referees and a cover letter explaining your interest in the position to g.goodhill(a)wustl.edu. Review of applications will begin immediately. Potential graduate students please note that there is an upcoming deadline of Aug 1st for applications to relevant Engineering graduate programs at WashU. Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Director, Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 4370 Duncan Ave. St Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd Linda J. Richards Edison Professor and Chair, Department of Neuroscience Director, McDonnell Center for Cellular & Molecular Neurobiology Washington University School of Medicine

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From Binghamton to Granada: COMPLEX NETWORKS 2026 is open for submissions
by Hocine Cherifi July 13, 2026

July 13, 2026

Dear colleagues, We would like to remind you that the 15th International Conference on Complex Networks and Their Applications (COMPLEX NETWORKS 2026) will take place in Granada, Spain, from December 2–4, 2026, with tutorials on December 1. This anniversary edition will continue the tradition of bringing together researchers from network science, complex systems, graph learning, computational social science, physics, computer science, mathematics, biology, economics, and many other fields. The program will feature keynote lectures by Alexandra Brintrup, Nitesh Chawla, Kimmo Kaski, Bruno Lepri, and Eckehard Schöll, as well as tutorials by Fariba Karimi and Huijuan Wang. Submissions are invited in two formats: · Full papers, up to 12 pages, for publication in the Springer proceedings; · Extended abstracts, up to 4 pages, for presentation at the conference and publication in the Book of Abstracts with ISBN. Selected contributions will also be considered for journal special issues. Submission deadline: September 2, 2026 Submission: https://cmt3.research.microsoft.com/COMPLEXNETWORKS2026/ Website: https://complexnetworks.org/ As a reminder, the Springer proceedings of COMPLEX NETWORKS 2025, held last December in Binghamton, are currently freely available. They provide a good overview of the diversity of contributions presented at the conference, across theory, methods, and applications of complex networks. Free access to the 2025 proceedings, Volumes 1–4, is available until July 30, 2026: https://drive.google.com/drive/folders/11_Xzh--IUPNwj6HE-Hzj8cIhXL-LLbMZ?us… We warmly invite you to submit your work and to share this call with colleagues, students, postdocs, and young researchers who may be interested. Best regards, Hocine Cherifi General Co-Chair, COMPLEX NETWORKS 2026 Join us at COMPLEX NETWORKS 2026 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Université Bourgogne Europe Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member 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/> Evolutionary Intelligence <https://link.springer.com/journal/12065>

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search for Assistant Professor in NeuroAI
by xaq＠cmu.edu July 13, 2026

July 13, 2026

Carnegie Mellon University (CMU) invites applications for a tenure-track Assistant Professor in the Neuroscience Institute from scholars working broadly at the intersection of Neuroscience and Artificial Intelligence. We welcome a wide range of research programs, provided they maintain a substantive connection to neuroscience through data, theory, or modeling. Examples of relevant research topics include but are not restricted to: generative models of brain data, AI-based analysis tools for neural activity or connectivity, explainable AI grounded in cognitive/neuroscience principles, human-AI alignment, normative agentic models of animal behavior, mechanistic models of memory or learning in neural networks, descriptive models of invariant representations and dynamics, and embodiment in both natural and artificial systems. The successful candidate will join a vibrant, collaborative environment spanning multiple departments at CMU. Our NeuroAI group leverages CMU’s world-class research in machine learning and AI, robotics, cognitive and systems neuroscience, neurotechnology, data science, engineering, and biological sciences. Joint appointments and courtesy appointments across departments are common in the Neuroscience Institute, and may be an opportunity for some candidates. CMU has a well-established structure for interdisciplinary collaboration in this domain, including specialized programs in neural computation and machine learning, and neurorobotics. The NI also encourages collaboration with industry and commercialization of new ideas. Aspiring entrepreneurs can be supported by a variety of business resources at CMU such as the Swartz Center and new entrepreneurship initiatives. Candidate responsibilities include establishing a visible, externally funded research program; teaching and mentoring in NI; recruiting and supervising both masters and Ph.D. students; and contributing to curricular innovation, including emerging initiatives, such as a new masters program in neural technologies. Information about the Neuroscience Institute can be found at https://www.cmu.edu/ni/.

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2-year Post-doc position on Autonomous Machine Learning / Computational Modeling of Cognitive Development
by Jochen Triesch July 10, 2026

July 10, 2026

The Frankfurt Institute for Advanced Studies (FIAS) is looking for a Postdoctoral Researcher (f/m/d) in the area of: Autonomous Machine Learning / Computational Modeling of Cognitive Development. The primary goal is to develop computational models that autonomously learn abstract representations and models of the world and ways to interact with it in and open-ended fashion from self-motivated physical interactions. Relevant keywords include: autotelic learning, open-ended learning, continual learning, intrinsic motivation, causality, compositionally, hierarchy, modularity. Please find links to some of our recent publications at the bottom. Your profile We are seeking an outstanding and highly motivated postdoc for this position. Applicants should have obtained a PhD in Machine Learning, Cognitive Science, Robotics, or related field. The ideal candidate will have excellent programming and analytic skills and a broad knowledge of machine learning and/or cognitive science. A strong interest in open-ended learning systems and human cognitive development is important. About FIAS The Frankfurt Institute for Advanced Studies (FIAS) is a hub for theoretical and computational research dedicated to solving complex scientific challenges. Our institute is located on the science campus of Goethe University Frankfurt (Campus Riedberg). Our fellows pursue interdisciplinary approaches to address fundamental questions in the various areas of natural sciences with an emphasis on biologically inspired computing. The working language of the institute is English. The position We offer a 2-year fulltime position in the lab of Prof. Dr. Jochen Triesch at the Frankfurt Institute for Advanced Studies (FIAS). Salary is based on TV-H E/13. FIAS is committed to fostering a workplace culture that promotes equality, diversity, and inclusion. We strongly encourage applications from qualified individuals regardless of gender, nationality, ethnic or social origin, religion, disability, age, or sexual orientation. Severely disabled persons with equal qualifications will be given priority. Your application Please submit your application in a single pdf file including: • a cover letter including the (expected) date of your PhD and your desired starting date, • a statement of research interests, • your CV with publication list, • contact information for at least two references. by 8 August, 2026 via our online portal: https://jobapplication.hrworks.de/de?companyId=amb4af72&id=efcd33 For further questions, please contact: Scientific issues: Prof. Dr. Jochen Triesch (triesch(a)fias.uni-frankfurt.de) Administrative issues: Meike Taplik (hr(a)fias.uni-frankfurt.de) -- Prof. Dr. Jochen Triesch Johanna Quandt Chair for Theoretical Life Sciences Frankfurt Institute for Advanced Studies and Goethe University Frankfurt Some relevant recent papers: https://ieeexplore.ieee.org/abstract/document/11204381 https://onlinelibrary.wiley.com/doi/full/10.1111/desc.70211 https://link.springer.com/chapter/10.1007/978-3-031-73226-3_4 https://onlinelibrary.wiley.com/doi/full/10.1111/desc.70231 https://www.nature.com/articles/s41467-025-64234-z

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Workshop at CNS2026: applications of detailed microcircuit models
by Etay Hay July 9, 2026

July 9, 2026

Workshop: Detailed models of brain microcircuit activity and signals in clinical applications July 15, 2026, 9:00am-12:30pm ADT At CNS 2026 conference, Halifax, Canada Speakers: Etay Hay Assistant Professor, Centre for Addiction and Mental Health, University of Toronto Heng Kan Yao Postdoc, Centre for Addiction and Mental Health, University of Toronto Salvador Dura-Bernal Associate Professor, State University of New York (SUNY) Downstate Katharina Duecker Postdoc, Brown University Alexandre Guet-McCreight Postdoc, Centre for Addiction and Mental Health, University of Toronto Brain function is mediated by neuronal microcircuits with specific connectivity between neuron types, and it is increasingly evident that altered microcircuitry underlies deficits in brain disorders such as depression and schizophrenia, and in aging and Alzheimer’s. However, our ability to monitor the microcircuitry in living humans is limited, meriting the use of detailed computational simulations to overcome experimental limitations in linking the microcircuit mechanisms with altered cortical activity, functional deficits and biomarkers in clinically-relevant brain signals. This workshop will showcase the latest efforts from leading groups in large-scale neuronal microcircuit modeling of spiking activity and signals such as EEG and MEG. The workshop will present diverse data-driven microcircuit modeling approaches that integrate neuronal, synaptic and functional data, and the different simulation tools used to generate activity and brain signals from the models. The workshop will highlight clinical applications of the models in establishing target mechanisms for treatment, and estimating microcircuit mechanisms from clinical signals in patient data with machine learning to improve diagnosis. This workshop aims to foster the exchange of methods and ideas, and offer new insights on clinical applications of simulated large-scale cortical microcircuits. CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout fichier qui y est joint, est reserve à l'usage exclusif du destinataire visé et peut contenir des renseignements confidentiels et privilégiés. Toute lecture, utilisation, divulgation ou distribution non autorisée est interdite. Si vous n'êtes pas le destinataire visé, veuillez en aviser l'expéditeur par retour de courriel et détruire toutes les copies du message original.

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[jobs] Computational Neuroscientist / Electrophysiology Data Analysis Engineer at MaxWell Biosystems (Zurich, Switzerland)
by Jan Müller July 8, 2026

July 8, 2026

Dear all, We are looking for a Computational Neuroscientist / Electrophysiology Data Analysis Engineer to join MaxWell Biosystems in Zurich, Switzerland. If you enjoy neural data analysis, statistical modeling, MEA-based extracellular electrophysiology, spike sorting, and developing software tools used by neuroscientists around the world, we would love to hear from you. MaxWell Biosystems develops high-density microelectrode array (HD-MEA) platforms for neuroscience research and drug discovery. Our technology combines custom CMOS sensors, FPGA-based acquisition hardware, and the MaxLab Live software platform to record, analyze, and visualize large-scale neural activity at high spatial resolution. As part of our interdisciplinary team, you will help develop the next generation of neural data analysis tools for our platform. Your Mission: - Develop and enhance robust pipelines for neural data analysis, including statistical analysis, spike sorting, and feature extraction - Evaluate and integrate state-of-the-art methods from computational neuroscience, machine learning, and statistics - Collaborate with neuroscientists and electrophysiologists to translate scientific challenges into practical software solutions - Develop APIs and software tools that simplify large-scale electrophysiology data analysis - Help shape the future of our analysis software by contributing your own ideas and technical expertise Your Profile: - Background in computational neuroscience, neuroengineering, or a related field - Hands-on experience analyzing extracellular MEA recordings is required - Experience with statistical analysis and modeling - Strong understanding of neural spike data, extracellular electrophysiology, and neural signal processing - Experience with spike sorting and neural data analysis tools (e.g. SpikeInterface, Kilosort, SpyKING CIRCUS, Phy) is a strong plus - Strong programming skills in Python; experience with C++ is a plus - Familiarity with Linux and scientific software development - Enjoy writing clean, maintainable code - Experience with AI-assisted coding tools (e.g. Claude) is a plus - Excellent communication skills and enthusiasm for working in an interdisciplinary team Why Join MaxWell Biosystems? Join a multidisciplinary team of neuroscientists, software engineers, and hardware developers working on cutting-edge HD-MEA technology for neuroscience research and drug discovery. Your work will directly contribute to software tools used by researchers around the world to analyze large-scale neural recordings. Apply: If this sounds like a role you would enjoy, we would love to hear from you. Please send your CV, a brief cover letter, and relevant transcripts to hr(a)mxwbio.com More details: https://www.mxwbio.com/open-position/computational-neuroscientist-electroph… Best regards, Jan -- Jan Müller, Ph.D. | CTO MaxWell Biosystems AG | Albisriederstrasse 253 | CH-8047 Zurich | Switzerland email: jan.mueller(a)mxwbio.com | web: www.mxwbio.com

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