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Fully-funded PhD position in neuroimaging studies at USC
by Z S Nov. 3, 2026

Nov. 3, 2026

Dear all, Description: Dr. Sha’s lab (https://shazhiqiang.wixsite.com/sha-lab) at the University of South Carolina is seeking *PhD students in neuroimaging studies *in the Department of Psychology. Our lab is affiliated with the Carolina Autism & Neurodevelopment Center, the Institute for Mind & Brain, and working closely with the McCausland Center for Brain Imaging in Columbia, center of SC Metropolitan Statistical Area. Our lab explores the mechanisms of atypical brain development and neurodevelopmental disorders (e.g., autism spectrum disorders) by leveraging computational modeling (e.g., deep learning models) to bridge neural circuitry, exposure (e.g., early life adversity) and psychopathological phenotypes, and treatment outcomes. These innovative projects will leverage state-of-the-art machine learning models and neuroimaging, supported by the brand-new Brain Imaging Center (with 3T and 7T MRI scanners) and the Biobehavioral Research Center at the University of South Carolina. This position provides an excellent opportunity for a self-motivated student to gain hands-on experience with neuroimaging (e.g., MRI) and biomedical research techniques. The candidate will have full access to rich in-house and public datasets, and advanced neuroimaging platforms. Our lab fosters a collaborative and productive environment, and we actively support PhD students in generating high-quality research publications, applying for fellowships and securing their future career paths. Key roles: · Data analysis; present results and publish papers under the PI’s supervision · Keep up-to-date on relevant studies and methods, and actively discuss them with the PI · Present your work at national and international conferences Requirements: · Bachelor’s or Master’s degree in a relevant field (e.g., neuroscience, math, data science, biostatistics, biomedical engineering) · Experience with neuroimaging MRI data analysis is preferred. · Candidates with coding experience are preferred. How to apply: Please submit your CV to Dr. Sha (zsha(a)mailbox.sc.edu)

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Fwd: World wide VVTNS series (7th season): November 4 2026 |Learning to Oscillate: Hebbian Plasticity Imprints Limit Cycles in Neural Networks| Pierfrancesco Urbi IPhT, Saclay France
by David Hansel Nov. 1, 2026

Nov. 1, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Pierfrancesco Urbi IPhT, Saclay France on the topic of Learning to Oscillate: Hebbian Plasticity Imprints Limit Cycles in Neural Networks The lecture will be held on Zoom on November 4, 2026 at *11:00 am ET * To receive the link: https://www.wwtns.online/register-page *Abstract: * Oscillatory activity is a hallmark of brain dynamics, yet how neural circuits learn to generate rhythmic patterns through biologically plausible mechanisms remains an open question. In this work, we investigate high-dimensional, non-linear dynamical systems—prototypical models of recurrent neural networks—exposed to incoherent periodic inputs and Hebbian-like synaptic plasticity. Our analysis reveals a striking phenomenon: depending on the interplay between the strength of the periodic drive and synaptic plasticity, the system’s phase diagram exhibits a regime where, once both inputs are removed, the network spontaneously settles into a limit cycle . This demonstrates that periodic drives can "imprint" lasting rhythmic patterns into the network’s connectivity, effectively teaching it to oscillate autonomously. Using dynamical mean-field theory (DMFT) and finite-size numerical simulations, we characterize this memorization phase , where the system retains a "memory" of the rhythm. We identify distinct dynamical attractors—chaotic, fixed-point, and limit cycle phases—and show that the limit cycle’s robustness depends on the metabolic time window between stimulation and plasticity halting. This work bridges the gap between driven and autonomous dynamics, offering a theoretically tractable yet biologically inspired mechanism for rhythm learning.

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Assistant Professor position at University of Arizona, Department of Philosophy, Consciousness Studies/ Philosophy of Mind
by Charles, Andrew Vincent - (andrewvcharles) Oct. 31, 2026

Oct. 31, 2026

Job category: Junior faculty / Tenure-track or similar Consciousness studies (construed broadly), or philosophy of mind and the philosophy of at least one special science relevant to the interdisciplinary study of consciousness such as cognitive science, psychology, neuroscience, AI, linguistics, or physics. AOC :Open Workload: Full time Vacancies 1 Organization's reference number: req27296 Location: Tucson, Arizona, United States Start date August 2027 Job description: The Department of Philosophy at the University of Arizona invites applications for a tenure track position at the rank of Assistant Professor, specializing in research on consciousness. In addition to candidates with a research focus on traditional philosophical questions regarding consciousness, we also encourage applications from candidates with strong research programs involving consciousness-adjacent areas of scientific inquiry. The Department seeks a researcher and teacher to contribute to its emerging interdisciplinary degree programs in Consciousness and to the overall philosophical life of the department. Candidates must have earned a PhD in Philosophy or another field relevant to consciousness research by the date of employment. Applicants whose PhD is not in Philosophy should include clear evidence of their research and teaching qualifications pertinent to a leading PhD program in philosophy. All applicants must demonstrate evidence of a commitment to undergraduate and graduate teaching. The standard teaching load in the department is 2 courses per semester. The individual hired will be expected to teach half of their courses at the undergraduate and graduate level in the philosophy of consciousness, and in other core related topics such as those listed in the AOS description; or also e.g. general philosophy of science; philosophy of biology; the philosophy of religion; neuroethics; AI ethics; or aesthetics. The individual hired will also be expected to engage actively in scholarship and participate in departmental, college, and university service, including participating actively in the long-established Center for Consciousness Studies, whose role is now expanding as a cross-disciplinary university center for both research and teaching. They will also be expected to participate actively in the graduate and undergraduate degree programs in Cognitive Science. The University of Arizona has a long history as a pioneer in the development of consciousness studies. Recently, the university has received significant donor support to create its new educational programs in consciousness studies for undergraduates and graduate students. To date we have created a unique undergraduate curriculum in consciousness studies, with increasing numbers of students; a parallel graduate program is under development. The programs now have an endowed chair in this area, with annually increasing funds for novel collaborative projects, with established programs in the cognitive sciences, information science, and neuroscience, among others. Applications should be submitted by November 7, 2026 for full consideration and include the following documents: • A brief cover letter • A curriculum vitae • A research statement, of no more than 2 pages • A statement of teaching interests and philosophy, of no more than two pages • Evidence of teaching excellence • A writing sample • At least three and no more than four letters of reference. Applicants with a PhD in a field other than Philosophy should be sure to have letters from at least two philosophers. For any questions please contact Dennis Tamblyn dtamblyn(a)arizona.edu. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here. https://talent.arizona.edu/ How to apply Application type: Online Instructions Letters of Recommendation can be submitted the following ways: 1. Attach the letters as a single document and upload to the application. 2. Email the letters directly to Dennis Tamblyn, dtamblyn(a)arizona.edu. 3. Send the letters through Interfolio to Dennis Tamblyn, dtamblyn(a)arizona.edu. Web address to apply https://arizona.csod.com/ux/ats/careersite/4/home/... Deadline for full consideration: November 7, 2026, 11:59am MST Hard deadline No deadline specified (applications considered on an ongoing basis) Contact Web address for more information https://philosophy.arizona.edu Contact name Dennis Tamblyn Contact email dtamblyn @arizona.edu Contact phone 520-621-5045

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Graduate Program at the Center for Perceptual Systems
by Mary Hayhoe Oct. 30, 2026

Oct. 30, 2026

The Center for Perceptual Systems (CPS) at the University of Texas Austin is an exciting interdisciplinary center designed to foster communication and collaboration in the study of sensory systems, at the behavioral, neural, and theoretical levels. Members of the Center come from the Departments of Neuroscience, Psychology, and Computer Science and have strong expertise in the investigation of perception in the context of natural environments, and in the development of computational tools both for studying neural function and for modeling natural behavior. We encourage applications from PhD candidates with particular interests in these domains. CPS Training Program Faculty Thomas Elston: Cognitive control, decision-making, computational psychiatry Robbe Goris: Visual perception, neural computation, perceptual decision-making. Mary Hayhoe: Eye movements, visual attention, and visuo-motor coordination. Lori Holt: Auditory perception, cognition, learning and attention. Jarrod Lewis-Peacock: Working memory, cognitive control, memory regulation. Franco Pestilli: Visual system connectivity and white matter mapping. Nicholas Priebe: Intracellular recording, 2 photon microscopy and visual neurophysiology. Thibaud Taillefumier: Computational and theoretical neuroscience. Xuexin Wei: Computational and theoretical neuroscience, visual perception. Chen Yu: Early sensory-motor development and learning, visual attention, visuo-motor coordination and egocentric scene statistics. Yuke Zhu: 3D computer vision, robot perception, and embodied AI. Graduate trainees come from a range of home departments and programs, most commonly from the Interdisciplinary Neuroscience Program, the Psychology Department, and Computer Science. Graduate admissions are through the participating departments listed below, together with application deadlines. https://inp.neuroscience.utexas.edu/ Deadline: Nov 15th https://liberalarts.utexas.edu/psychology/ Deadline: Nov 15th https://www.cs.utexas.edu/graduate/degrees-and-programs Deadline: December 15th Mary Hayhoe Center for Perceptual Systems University of Texas Austin 108 E. Dean Keeton Blvd, Stop A8000 Austin TX 78712-1043 hayhoe(a)utexas.edu

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Postdoc Position at Radboud University (Nijmegen) in NeuroAI: Biologically Grounded Neural Networks for Cognition
by Paul Tiesinga Oct. 29, 2026

Oct. 29, 2026

Postdoc Position at Radboud University (Nijmegen) in NeuroAI: Biologically Grounded Neural Networks for Cognition _Can you help designing cognitive architectures to make brain implants smart in an international and interdisciplinary team involving the top neuroscience institutes in the Netherlands and thereby (ultimately) contribute to improve the life of patients?_ Brain implants are, for the most part, fixed-function devices. The EBRAINS-NEUROTECH infrastructure is building a tool chain that changes this: neural networks that perform the perceptual and cognitive processing an implant needs, run on-device, and can be adapted by the experimenter. You will build the core of that tool chain: a set of neural network modules for perception and cognition, grounded in what we know about the brain's own mechanisms. For this position you will develop NeuroAI-in-practice: a set of neural network modules that can be easily used and adapted by an experimental user, while also giving publishable scientific insights in and of themselves. Two use-cases, involving processing for vision implants and implants for cognitive restoration, will guide the work. These networks also have to run on-device. Together with a postdoctoral researcher from the Centre for Mathematics and Computer Science (CWI), you will translate the designs to a neuromorphic architecture. Does this sound like you? * You are a scientific programmer or postdoctoral researcher with excellent programming skills and a strong interest in NeuroAI. * You have a PhD degree in a quantitative field, such as physics, mathematics, computer science, engineering or computational or theoretical neuroscience. * You have experience with programming in Python and C in combination with deep learning tools such as PyTorch, TensorFlow, and JAX. * You have a background in neuroscience, preferably on mechanisms for cognitive processes, or a strong desire to obtain such a background. This position is physically hosted at the Neurophysics department of the Donders Institute at Radboud University. The work is part of the Software Platform of the EBRAINS-NEUROTECH infrastructure, involving teams at the University of Amsterdam (Dr Jorge Mejias), CWI (Prof. Sander Bohte) and Radboud University (Prof. Paul Tiesinga). To apply for this job please consult the Academic Transfer link: https://www.academictransfer.com/en/jobs/365079 For more information contact Paul Tiesinga at p.tiesinga(a)science.ru.nl

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ANNOUNCING the 2025 Best Illusion of the Year Contest Winners AND ACCEPTING SUBMISSIONS for the 2026 CONTEST!
by smart＠neuralcorrelate.com Oct. 29, 2026

Oct. 29, 2026

Dear Illusion Enthusiasts, Voters around the globe chose the Best Illusions of 2025 from the TOP TEN Finalists competing in the 20th edition of the Best Illusion of the Year Contest <https://illusionoftheyear.com/> (hosted by the Neural Correlate Society and supported by the Museum of Illusions <https://www.museumofillusions.com/> ). The TOP THREE winning illusions were revealed on Tuesday, October 27th, 2026. First Prize and a $3,000 award went to "Cogs in a Machine," by Jacky Z. J. Yueh and Joan Danielle K. Ongchoco, Canada. Second Prize and a $2,000 award went to "9 Purple Dots," by Hinnerk Schulz-Hildebrandt, United States. Third Prize and a $1,000 award went to "The Hole Truth," by Matt Pritchard, United Kingdom. This year's illusions are making headlines! Read The Washington Post's article featuring several of the illusions that just competed in the Best Illusion of the Year Contest: <https://www.washingtonpost.com/health/2026/10/27/how-this-years-best-optica l-illusions-trick-your-brain/> How this year's best optical illusions trick your brain. If you enjoyed the spectacular winning and finalist illusions, please consider making a tax-deductible donation <https://www.paypal.com/webapps/shoppingcart?flowlogging_id=d2461f180023b&mf id=1607894519576_d2461f180023b#/checkout/openButton> to the Best Illusion of the Year Contest. We rely on your generous help to continue to share the wonders of illusion with people of all ages and backgrounds, all over the world. We are now accepting submissions for the 21st edition of the Best Illusion of the Year Contest! If you have created a novel, mind-bending illusion, we invite you to share it with the world. Don't miss the opportunity to be part of next year's TOP TEN illusions and compete for international recognition and cash prizes. Contestants are invited to submit 1-minute YouTube videos featuring novel illusions (unpublished or published no earlier than 2025) of all sensory modalities (visual, auditory, etc.) and/or cognitive nature. Novel variants of known illusions are welcome. The content of the 1-minute video presenting your illusion is solely up to you, and the only requirement is that it wows all viewers! Some examples include, but are not limited to: * A slide presentation, or succession of images, with a voice over (and/or written text, if you prefer) * A video of yourself describing your illusion * A video animation/theatrical performance of your illusion An international panel of impartial judges will rate all the videos and narrow them down to the TOP TEN. Then, online voters around the world will choose their favorite illusions from the TOP TEN finalists. The TOP THREE winners will receive cash prizes: $3,000 USD for first place; $2,000 USD for second place, and $1,000 USD for third place. The Judge Panel will rate illusions according to: * Significance to our understanding of the human mind and brain * Simplicity of the description * Sheer beauty * Counterintuitive quality * Spectacularity Submissions will be held in strict confidence by the Judge Panel. Only the TOP TEN illusions will be posted online, to allow worldwide voting. Participation in the Best Illusion of the Year Contest does not preclude you from also presenting or submitting your work for publication elsewhere. By participating in the Best Illusion of the Year Contest you agree to have your illusion posted on the Contest website, if selected among the TOP TEN, and included in press releases and other promotional materials/fundraising initiatives for the Contest. You (and your co-authors, if appropriate) will retain the full copyright of your illusion and receive full credit as illusion creator(s). Illusions submitted to previous editions can be re-submitted to the 2026 Contest, as long as they meet the above requirements and were not among the TOP TEN finalists in previous years. You can send your 1-minute video to Susana Martinez-Conde via email ( <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com) until December 14th, 2026. On behalf of the Executive Board of the Neural Correlate Society: Jose-Manuel Alonso, Stephen Macknik, Susana Martinez-Conde, Luis Martinez, Xoana Troncoso, Peter Tse ---------------------------------------------------------- Susana Martinez-Conde, PhD Author, <x-msg://2/championsofillusionbook.com> Champions of Illusion and Sleights of Mind Professor of Ophthalmology, Neurology, and Physiology & Pharmacology State University of New York (SUNY) Downstate Health Sciences University 450 Clarkson Ave, Brooklyn NY 11203, USA Email: <mailto:smart@neuralcorrelate.com> smart(a)neuralcorrelate.com Phone: <tel:%2B1%20718-270-4520> +1 718-270-4520 http://smc.neuralcorrelate.com

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Diagnosing inconsistent partial-cue recall in a small recurrent LIF network
by 오성민 Oct. 28, 2026

Oct. 28, 2026

Hello, I’m developing an independent, AI-assisted computational modelling project. My immediate goal is reliable partial-cue recall that depends on learned recurrent connections. I would appreciate advice on the first diagnostic to prioritize, or a published working model suitable for comparison. The network has 24 input channels, 96 expansion neurons, 48 excitatory recurrent memory neurons, and a fixed 32-neuron LIF readout. Input-to-expansion connections learn normalized input/spike coactivity during storage. Recurrent memory weights also learn; all weights are frozen during evaluation. The protocol presents a six-channel pattern P for 1,000 ms, then zero input for 500 ms, followed by three of P’s channels continuously for 200 ms. The current endpoint is cosine similarity between readout spike counts and a full-P reference recorded before learning. A paired control restores the same post-storage checkpoint and resets only recurrent weights to their initial values. Input-pathway weights, neural state, retained traces, and initial RNG state are preserved. A separate recurrent-learning-off condition still permits input-pathway learning during storage. Across three seeds, learned-minus-reset cosine differences were +0.003414, +0.003999, and −0.037353. This did not meet the specified robustness criteria. In the negative case, learned and reset branches had identical per-neuron memory spike counts, but different spike timings. Five readout spikes were absent in the learned branch; its score was 0.842399 versus 0.879752 after reset. Also, naïve readout responses to two overlapping full patterns were very similar in two seeds, with P/Q cosines of 0.97846 and 0.99618; the third was 0.77380. These observations do not establish successful recall hidden by the readout. Some implementation details: - Current-based LIF, dt=1 ms, tau=20 ms, rest/reset=−65, threshold=−50, refractory period=2 ms. - Recurrent connections are directed, excitatory-only, approximately 60% dense, with no self-connections and a one-step delay. Weights start at 0.6 and are clipped to [0,8]. - The learning rule examined here is dW[j,i]=0.06*spike[j]*pre_trace[i]−0.025*post_trace[j]*spike[i]. Both traces decay with a 20-ms time constant; updates use decayed traces before adding current spikes. - Expansion-to-memory and memory-to-readout projections each supply 12 inputs per postsynaptic neuron, weighted 180 and 120 respectively. Which diagnostic would you prioritize to localize the bottleneck between learned recurrent completion and its measurement through the fixed readout, while accounting for the learned input pathway? What contrasting outcomes would make that diagnostic informative? A published LIF associative-memory model with a comparable partial-cue test would be particularly helpful. I am seeking a practical next step toward a working circuit, while keeping the existing endpoint and negative findings unchanged. Thank you. 오성민 Independent researcher Unaffiliated

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Postdoc Fellowships at WashU
by Goodhill, Geoffrey Oct. 28, 2026

Oct. 28, 2026

POSTDOCTORAL FELLOWSHIPS AVAILABLE AT WASHINGTON UNIVERSITY IN ST LOUIS The Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) at Washington University in St Louis invites applications from outstanding Postdoctoral Fellows to work at the interface between theoretical and experimental neuroscience labs at WashU. Deadline for applications is Dec 1st 2026. The CTCN is a joint initiative between the Schools of Medicine, Engineering, and Arts and Sciences at WashU, and provides a hub for neuroscientists to collaborate with mathematicians, physicists and engineers to find creative solutions to some of the most difficult problems currently facing neuroscience and artificial intelligence. Each CTCN Postdoctoral Fellow is based in at least two labs, but also has the opportunity to seek out new collaborations which help build new connections within the WashU community. We are looking for people with drive, independence and outstanding prior achievement, who are committed to leveraging interdisciplinary collaboration to drive forward the field of theoretical and computational neuroscience. Washington University in St Louis is ranked =6 worldwide for Neuroscience and Behavior by USNews. Salary for CTCN Fellows is $80,000 plus $10,000 for research costs and travel. In addition, WashU offers excellent benefits and comprehensive access to career development, professional and personal support. The St Louis metropolitan area has a population of almost 3M and is rich in culture, green spaces and thriving music and arts scenes, with a highly accessible cost of living. For more details, including how to apply, please see https://ctcn.wustl.edu/postdoc-fellows Professor Geoffrey J Goodhill CTCN Director Departments of Developmental Biology and Neuroscience Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

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[Jobs] two 4 years PhD positions with Prof. Laurenz Wiskott at Ruhr University Bochum, Germany, for modeling episodic memory in humans
by Laurenz Wiskott Oct. 28, 2026

Oct. 28, 2026

Germany : Ruhr University Bochum : Faculty of Computer Science : Institute of Neuroinformatics : Theory of Neural Systems Application platform: https://jobs.ruhr-uni-bochum.de/en/jobposting/b03ed1dd010514c25ed288e12387d… In order to fill a fixed-term position in part-time (29.87 hours/week = 75%) 01.01.2027 pending funding approval, we are looking for candidates (m/f/x) for two Doctoral Positions. The Institute of Neuroinformatics is a research institute of the Faculty of Computer Science at the Ruhr University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. Bochum is one of the centers of episodic memory research with a coherent framework developed within the DFG Research Unit 2812 "Constructing Scenarios of the Past" (https://for2812.rub.de/) combining psychology, neuroscience, philosophy, and computational neuroscience. In order to fill two fixed-term positions in part-time (29.87 hours/week = 75%) from the 1st of January 2027, pending funding approval, we are looking for 2 doctoral students in the research group of Professor Laurenz Wiskott. The research focuses on modeling generative episodic memory within a large, highly interdisciplinary research consortium in close collaboration with experimental partners. The methods used draw from neural network theory and machine learning. Your tasks: * Contributing to the development of an integrated systems level model of generative episodic memory. * Integrating this model with other aspects of cognition, such as planing and reasoning. * Modeling experimental data. * Communication with experimental partners. * Publication of results. Your profile: * Very good Master degree in physics, mathematics, computer science, engineering, or a related field. * Interest in interdisciplinary research in the area of neuroscience. * Good programming and mathematical skills. * Basic knowledge in machine learning. Advantageous: * Experience in modeling. * Experience in interdisciplinary projects. * Programming skills in Python. We offer: * Challenging and varied tasks with a high level of independence * Collaboration in a committed and appreciative team * Extensive training and professional development opportunities * Options for flexible working (mobile working and teleworking) * An interesting interdisciplinary environment in the field of theoretical brain research / machine learning. * Freedom to shape the project yourself. * Infrastructure that facilitates close integration into the institute and the research group. * Opportunity to pursue a Ph.D. Further information: The position is salaried and based on the collective agreement of the Länder (TV-L). If the personal and collective agreement requirements are met, the employee will receive pay grade E13 TV-L. Further information can be found at https://oeffentlicher-dienst.info/ (in German). The place of work is Ruhr University Bochum. If the position is funded by third-party funds the employee has no teaching obligation. RUB sees itself as a university with an international presence. The campus languages are German and English. Competence in at least one of the two languages and the willingness to learn the other are a prerequisite. RUB provides corresponding free courses for employees. German language courses are offered by the University Language Center (ZFA) in the field of German as a Foreign Language (DaF). https://www.daf.ruhr-uni-bochum.de/daf/mitarbeitende/index.html.en The Staff Council has the right to participate in all selection interviews. At the request of a candidate (m/f/x), it will ensure its participation in the entire procedure. Please contact wpr(a)rub.de. The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is Ruhr-Universität Bochum’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome. Contact persons for further information: Laurenz Wiskott , Tel.: +49 234 32 27997 Travel costs, accommodation costs and loss of earnings or other application costs for job interviews can unfortunately not be reimbursed. We look forward to receiving your application via our online application portal by 2026-11-09. Please make sure to mention the reference number ANR 6248: https://jobs.ruhr-uni-bochum.de/en/jobposting/b03ed1dd010514c25ed288e12387d…

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Postdoctoral contract at Instituto de Neurociencias (Alicante, Spain) - up to 2 years
by Encarni Marcos Sanmartin Oct. 28, 2026

Oct. 28, 2026

Dear colleagues, We are looking for a *postdoctoral researche*r to join our lab, the Plasticity of Brain Networks at the Institute for Neurosciences (CSIC–UMH) in Alicante, Spain. Please find the full announcement attached. I would be grateful if you could share it with anyone who might be interested. One of our research lines focuses on studying how different brain regions interact to shape our choices, and how the body, and movement in particular, influences what we decide. We combine behavioral tasks in animal models,* in vivo* electrophysiology, and computational modeling. The postdoc will: • Train animals in decision-making tasks • Perform in vivo electrophysiological recordings • Analyze behavioral and neural data, in close interaction with computational modeling *Requirements*: PhD in Neuroscience, Biology, Psychology, Physics, Engineering, or a related field; demonstrable hands-on experience in electrophysiology; accreditation for animal experimentation; good written and spoken English. *Valued*: experience training animals in behavioral tasks and programming skills (Python/MATLAB). We *offer* a full-time contract for up to 2 years, with salary according to UMH scales, in a Severo Ochoa Center of Excellence a few minutes from the Mediterranean Sea. To apply, please send your CV, a cover letter, and contact information for two references to emarcos(a)umh.es. Applications will be reviewed on a rolling basis until the position is filled. Direct link to the offer: https://in.umh-csic.es/es/ofertas/postdoctoral-position-2-years-neural-mech… Feel free to contact me with any questions. Best regards, Encarni Marcos Plasticity of Brain Networks Lab Institute for Neurosciences (CSIC–UMH) Alicante, Spain emarcos(a)umh.es

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