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Academic positions in Artificial Intelligence at the University of Surrey

by roman bauer

Dear all, We are pleased to announce three open academic positions in Artificial Intelligence at the University of Surrey, UK: Professor in Artificial Intelligence (NICE Research Group within the Computer Science Research Centre) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037526 Senior Lecturer in Artificial Intelligence (NICE Research Group within the Computer Science Research Centre) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037426 Professor in Artificial Intelligence (Centre for Vision, Speech and Signal Processing) https://jobs.surrey.ac.uk/Vacancy.aspx?ref=037626 Closing date: Sunday 13 September 2026 The School of Computer Science and Electronic Engineering is seeking to recruit internationally recognised researchers to strengthen its research and teaching in Artificial Intelligence. These appointments form part of a wider recruitment campaign and strategic investment across the Faculty: https://www.jobs.ac.uk/enhanced/linking/university-of-surrey-engineering-ph… The Professor and Senior Lecturer positions in Computer Science cover areas including Large Machine Learning Models, Neurosymbolic AI, Trustworthy Machine Learning, Natural Language Processing, and applications of AI and machine learning in automated reasoning, security, and software and systems development. Both posts are aligned with the Nature Inspired Computing and Engineering (NICE) Research Group within the Computer Science Research Centre. The Professor position within the Centre for Vision, Speech and Signal Processing focuses on leading growth in frontier AI, including multimodal foundation models, machine learning, agentic, people-centred and sustainable AI, with applications spanning human and animal health, biosciences, creative industries, sustainability, robotics and autonomous systems. The School is home to two established research centres with substantial expertise in AI and machine learning: the Computer Science Research Centre and the Centre for Vision, Speech and Signal Processing. Surrey has an established international reputation in AI research, ranking first in the UK for computer vision and among the top five for AI, computer vision, machine learning, robotics and natural language processing according to CSRankings.org. The School was also ranked seventh in the UK for Computer Science research outputs in REF2021. Computer Science and CVSSP are central to the Surrey Institute for People-Centred AI, a pan-University initiative bringing together AI research and expertise across health, engineering, social and behavioural sciences, business, law and the creative arts. The Institute leads a portfolio of more than £100 million in grant awards, including major activities in healthcare and the creative industries, and two doctoral training programmes supporting more than 100 PhD researchers. Informal enquiries concerning the Computer Science positions may be directed to Professor Brijesh Dongol at b.dongol(a)surrey.ac.uk. Enquiries concerning the CVSSP position may be directed to Professor Adrian Hilton at a.hilton(a)surrey.ac.uk. Our staff and students come from around the world, and we are proud of our friendly and inclusive culture. The University is committed to building a diverse community, and applications from under-represented groups are particularly encouraged. Please share these opportunities with potentially interested candidates and across your networks. Best regards, Roman *Roman Bauer, Ph.D.* Senior Lecturer | Head of the NICE Research Group BioDynaMo Spokesperson (www.biodynamo.org) *A software suite to enable simulations of large, complex systems for research or policy making* *Computer Science Research Centre* University of Surrey | Guildford, UK r.bauer(a)surrey.ac.uk | ORCID <https://orcid.org/0000-0002-7268-9359> | LinkedIn <https://www.linkedin.com/in/roman-bauer-05176094/> * Watch the **BioDynaMo introduction video* <https://youtu.be/N6Kzc_AadyI?si=zHymOvrlR3wzAbCf>

Aug. 27, 2026

Postdoc Positions in Cognitive and Computational Neuroscience at Washington University in St. Louis

by Runnan Cao

The Multimodal Cognitive Neuroscience Laboratory, led by Dr. Runnan Cao at Washington University School of Medicine in St. Louis, invites applications for postdoctoral research associate positions. Our laboratory investigates the neural computations and network-level dynamics underlying visual perception and social cognition in neurotypical individuals and people with neurodevelopmental or psychiatric conditions, including autism and schizophrenia. We combine human intracranial electrophysiology, including iEEG and single-neuron recordings, with high-resolution fMRI, behavioral experiments, and computational modeling to determine how the brain transforms visual input into representations that support social perception and behavior. These positions offer a distinctive opportunity to join a new laboratory at a formative stage. The successful candidates will help shape its scientific direction, analytical infrastructure, collaborative culture, and multimodal research program. Research Projects will be tailored to each postdoctoral researcher’s expertise, interests, and career goals. Potential research areas include: Neural coding of faces and socially relevant visual information Neurocomputational mechanisms underlying visual perception and social cognition Neural coding and network-level dynamics associated with autism and schizophrenia Multimodal integration of iEEG, single-neuron recordings, high-resolution fMRI, and behavioral data Computational models linking neural activity to perception and behavior AI-enabled methods for analyzing complex multimodal neuroscience data Required Qualifications Applicants must have: A PhD or equivalent doctoral degree in neuroscience, cognitive science, psychology, biomedical engineering, computer science, or a related discipline by the appointment start date A strong research background in fMRI and/or electrophysiology Experience analyzing neuroimaging, neural, behavioral, or computational data Proficiency in scientific programming, particularly Python and/or MATLAB Evidence of research productivity appropriate to career stage Strong written and oral communication skills The ability to work both independently and collaboratively in an interdisciplinary environment Preferred Qualifications Experience in one or more of the following areas is desirable: Acquisition or analysis of 7T fMRI data Human intracranial EEG, ECoG, depth-electrode, or single-neuron recordings Advanced statistical methods, neural signal processing, or network neuroscience Machine learning or deep learning applied to neural and behavioral data Multimodal integration of neuroimaging, electrophysiological, and behavioral data Agentic AI or AI-assisted scientific workflows Development of reproducible data-processing pipelines, workflow systems, or reusable computational tools Candidates who have deep expertise in one methodological area and are eager to develop complementary skills are strongly encouraged to apply. Mentoring and Professional Development Each postdoctoral researcher will work with Dr. Cao to develop an individualized research and career-development plan. Training may include advanced fMRI and electrophysiological analysis, computational modeling, machine learning, scientific writing, grant preparation, project leadership, mentoring, and the development of reproducible research tools. Postdoctoral researchers will be encouraged to establish a clear area of scientific ownership, pursue external funding, build an independent scholarly profile, and develop the skills needed for their chosen career path. Why Join Our Laboratory? Postdoctoral researchers will have the opportunity to: Work with distinctive human intracranial and single-neuron datasets Develop expertise across complementary spatial and temporal scales of brain measurement Help establish the methods, workflows, and scientific culture of a growing laboratory Receive individualized mentoring in research strategy, scientific writing, grant development, and career planning Build collaborations spanning cognitive, computational, clinical, and systems neuroscience Pursue independent fellowships and develop a path toward scientific independence Present their work at national and international scientific meetings The laboratory is committed to rigorous and open science, intellectual curiosity, constructive collaboration, and an environment in which researchers with different backgrounds and methodological strengths can thrive. Why WashU and the Neuroimaging Labs? The laboratory is based in the Neuroimaging Labs Research Center <https://www.mir.wustl.edu/research/research-centers/neuroimaging-labs-resea…> at WashU Medicine’s Mallinckrodt Institute of Radiology. The NIL-RC brings together investigators, postdoctoral researchers, students, clinicians, engineers, and research staff from Radiology, Neurology, Psychiatry, and other departments. The center has a longstanding record of innovation in neuroimaging methods and has supported major scientific initiatives, including the Human Connectome Project and the Alzheimer’s Disease Research Center. Its research spans human cognition, functional connectivity, precision neuroimaging, brain development and aging, psychiatric and neurological disorders, brain parcellation, and imaging methodology. The WashU neuroimaging environment includes: A dedicated research MRI facility <https://www.mir.wustl.edu/research/core-resources/mri-facility/> with three Siemens PRISMA 3T scanners and experienced research imaging personnel A Siemens MAGNETOM Terra.X 7T MRI system <https://www.mir.wustl.edu/magazine/magnified-medicine-7t-comes-to-mir/> supporting ultra-high-resolution structural and functional imaging Internationally recognized expertise in functional connectivity, precision neuroimaging, brain mapping, neuroinformatics, and multimodal imaging Strong connections with Psychiatry, Neurology, Neurosurgery, Neuroscience, Psychological & Brain Sciences, Biomedical Engineering, and Computer Science Opportunities for clinical and translational collaboration in autism, schizophrenia, epilepsy, Alzheimer’s disease, and other neurological and psychiatric conditions A broad seminar, training, and professional-development community across WashU Medicine and the university This environment is especially well suited to researchers who want to connect fine-grained neural recordings with whole-brain imaging, behavior, and computational theory. How to Apply Applicants should email the following materials to Dr. Runnan Cao at r.cao(a)wustl.edu <mailto:r.cao@wustl.edu>: A cover letter describing the applicant’s research experience, methodological expertise, scientific interests, career goals, and potential fit with the laboratory A current curriculum vitae Contact information for two professional references; letters are not required with the initial application Please use the subject line: Postdoctoral Application – [Applicant Name].

Aug. 26, 2026

Call for Papers: Novel Insights and Approaches in Time-frequency Analysis

by alireza valizadeh

Dear colleagues, I am writing to share a Call for Papers for a new *Nature Collection in Communications Psychology*, *“Novel Insights and Approaches in Time-frequency Analysis,”* which is now open for submissions: https://www.nature.com/collections/ejbgajabei The Collection brings together new methodological and empirical advances in time-frequency analysis, with broad relevance to neuroscience and related fields. We would particularly welcome work introducing novel approaches, methods, or insights into the analysis and interpretation of time-varying neural signals. The Collection is co-edited by *Gabriele Gratton (University of Illinois Urbana-Champaign)* and *Alireza Valizadeh (IASBS)*. If you have research that may be a good fit, we would be very happy to consider your submission. Please see the Collection page for further details on the scope and submission process. Best wishes, Alireza Valizadeh and Gabriele Gratton ------------------------------------------------------Alireza Valizadeh*Professor * Theoretical Neuroscience lab, Institute for Advanced Studies in Basic Sciences (IASBS), Iran *Principal Investigator* Zapata-Briceño Institute of Neuroscience and Human Intelligence, Spain Tel: (+34) 603325584 valizadeh(a)gmail.com valizadeh(a)institutobz.org <valizadeh(a)humanismoyciencis.org> Web: https://www.institutobz.org/ <https://fundacionhumanismoyciencia.org/instituto-zapata-briceno/> http://www.iasbs.ac.ir/~valizade/index.html --------------------------------------------------------

Aug. 26, 2026

2 PhD positions for 4 years with focus on "Generative Episodic Memory" with Prof. Laurenz Wiskott, Germany, Bochum

by Laurenz Wiskott

From https://jobs.ruhr-uni-bochum.de/jobposting/854eabcb1786fa8b53af20c255cd9aea… Faculty of Computer Science : Chair: Theory of Neural Systems In order to fill a fixed-term position in part-time (29.87 hours/week = 75%) at the earliest possible date, we are looking for 2 2 Research associates (m/f/x) for 4 years with focus on "Generative Episodic Memory" The Institute for Neural Computation is a central research institute 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. The research focuses on (i) modeling generative episodic memory in close collaboration with experimental partners, with the goal of modeling experimental data and gaining a deeper understanding of memory processes; (ii) developing a hierarchical model of the visual system that supports a generative memory process. The first project will focus primarily on standard machine learning methods, such as Transformers. The second project aims to develop new methods inspired by the brain. Scope: part-time (75%) Duration: fixed-term, 4 Jahre Start: at the earliest possible date Apply by: 2026-09-14 Your tasks: (i) Further development of an existing system model of generative episodic memory in light of various experimental results. (ii) Development of a brain-inspired hierarchical model of the visual system that supports distributed generative memory processes. Modeling of experimental data. Communication with experimental partners. Publication of results. Teaching assistance equivalent to 3 SWS, in particular conducting a Python course and supervising student/Bachelor/Master projects. Your profile: Requirements: Very good Master degree in 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 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 E 13 TV-L. Further information can be found at https://oeffentlicher-dienst.info/ (in German). The place of work is Ruhr University Bochum. The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia). Applications (CV, transcript of records for MSc and Bsc, letter of motivation) should be sent as a single pdf file. 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: Prof. Dr. Laurenz Wiskott Tel.: +49 234 32 27997 Kathleen Schmidt Tel.: +49 234 32 27051 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 at https://jobs.ruhr-uni-bochum.de/en/jobposting/854eabcb1786fa8b53af20c255cd9… by 2026-09-14. Please make sure to mention the reference number ANR 6046.

Aug. 25, 2026

Spectral analysis in neuroscience course for non-specialists

by Axel Hutt

============================================================= Course: Spectral analysis of time series in neuroscience: Fundamental methods ============================================================= The 1-day course addresses fundamental aspects of spectral analysis without diving much into theory, just from a practical point of view. The aim is to provide a fundamental understanding of the different techniques out there to avoid mistakes, artefacts and to be able to choose the best technique for the own data. The course is planned like an interactive workshop, where we discuss analysis techniques and clarify open questions and possibly fill gaps of methodology understanding. The course content addresses non-specialists in mathematical analysis, e.g. researchers with education in neurobiology, medicine or psychology, but of course it is also open to theory-oriented researchers who intend to understand the practical side of spectral analysis in neuroscience. Possible topics to be discussed are, e.g. * Sampling theory * Fourier analysis and its possible artefacts, e.g. aliasing, spectral leakage * Time-frequency analysis (Short-Time Fourier Transform, Wavelet Transform, Hilbert Transform and Empirical Mode Decomposition) and its limits in applications * Synchronisation, coherence and Phase-Amplitude Coupling Event information: * Location: Bernstein Center Freiburg im Breisgau, Großer Hörsaal, Hansastr. 9a , 79104 Freiburg, Germany ( [ https://www.bcf.uni-freiburg.de/ | https://www.bcf.uni-freiburg.de ] ) * Date of course and time: Friday, November 27 2026, 9:15-15:45 * Registration : send an email to Axel Hutt (email address: first name.lastname at inria.fr) * Registration deadline: Monday, November 9 2026 * Registration fee: none, free of charge The course is supported by the Neurowissenschaftliche Gesellschaft ( [ https://www.nwg-info.de/ | https://www.nwg-info.de/ ] ). -- Dr. rer. nat. Axel Hutt Directeur de Recherche Equipe NECTARINE - INRIA Nancy Center at University of Lorraine Equipe MLMS - iCube Strasbourg Bâtiment NextMed , 2, rue Marie Hamm 67000 Strasbourg, France Team webpage: https://www.inria.fr/fr/nectarine

Aug. 25, 2026

[Hiring] Multiple positions in Italy: NeuroAI Researcher & Biosignal data collection at Silenzio SRL

by Matteo Ferrante

Dear comp-neuro community, I am writing on behalf of *Silenzio*, a newly founded startup developing a new generation of human–machine interfaces based on non-invasive neural and physiological signals. Our goal is to build systems that can decode human intent more directly than traditional interfaces. We are currently expanding our team and looking for researchers and engineers excited about neural decoding, NeuroAI, biosignal processing, and human–machine interaction. We are hiring for two roles: an *AI Research Scientist* and a *Biosignal Data Collection Specialist*. We believe that as machines become increasingly capable, the bandwidth of human-to-machine communication will become one of the key bottlenecks in how effectively we interact with them. Therefore, we are assembling an exceptionally talented international team and are actively seeking people who are excited to embrace our mission and help us build what we believe will be the future of interfaces. If this resonates with you, we invite you to explore our open roles listed below and consider joining us. If you are interested, please write to us at *jobs(a)silenzio.io <jobs(a)silenzio.io>* with a copy of your CV attached, mentioning *“AI Research Scientist”* or *“Biosignal Data Collection Specialist”* in your application. We would like to fill these positions on a rolling basis, starting in *fall 2026*. *1. AI RESEARCH SCIENTIST* *Job Responsibilities* Your core responsibility will be the modeling and software side of developing a novel human-machine interface device that decodes intent from neural, bio-, and physiological non-invasive signals. Concretely, you will: - Stay current with recent scientific literature in neuroAI - Implement and adapt existing models - Design and implement state-of-the-art decoding (and encoding) models for neural and bio-signals, capable of translating text, actions, and more broadly "intents" into instructions for machines - Reason from first principles to design novel solutions to open problems in human-machine interfaces, including new AI architectures and pipelines - Quality-check data and aggregate diverse datasets, both public and private - Preprocess neural data—multivariate time-series such as EMG, EEG, and invasive neural recordings—and standardize it into common formats - Integrate (or support the integration of) developed models into proprietary data-acquisition pipelines and decoding systems - Monitor and track experiments, and write documentation and scientific reports - Communicate and collaborate closely with the team, brainstorming ideas and implementation paths *Experience* - MSc in computer science, computational neuroscience, bioengineering, physics, mathematics, or a related field (PhD preferred) - A proven track record of designing, building, and shipping deep learning products—e.g., publications at top-tier venues (NeurIPS, ICLR, Nature-family journals, or similar) and/or the development and ideally deployment of AI models in real-world applications - Strong proficiency in Python and AI-oriented libraries such as PyTorch, Lightning, Hugging Face, and scikit-learn - A solid foundation in (bio-)signal processing, algorithms, and software engineering principles - Excellent communication skills, fluency in English, rigor, and the ability to work effectively with an international team Preferred: - Experience with EEG, EMG, or invasive neural recordings, and with data-collection pipelines - Experience designing, developing, or fine-tuning LLMs or ASR models - Experience with self-supervised learning and multi-GPU large scale training of deep learning models Bonus: - Basic web-app development skills, and a good understanding of and taste for design *Compensation* Gross annual salary (RAL) of €50k–€80k, determined by your job-related skills, experience, and relevant education or training. *Position* Full-time (40h/week), fully remote within Italy. Occasional on-site presence or travel is required—for integrating models into production systems and attending conferences and events. *2. BIOSIGNAL DATA COLLECTION SPECIALIST* *Job Responsibilities* We are looking for people to run EEG/EMG data acquisition end-to-end: co-designing experimental protocols, recruiting and welcoming participants, collecting signal data, and preparing it for analysis. We are recruiting across two distinct tracks—engineering-oriented and participant-facing. Apply to the one that fits you best. Concretely, you will: - Maintain and manage the inventory of all lab equipment, including tools and consumables - Co-design experimental paradigms and tasks for data collection - Handle participant recruitment, onboarding, compliance, briefing, and data collection - Set up the recording hardware (EMG, EEG) and manage hardware maintenance and quality control - Run and monitor large-scale experiments *Engineering track:* - Maintain and improve the data-collection backend and frontend, fixing bugs and issues as they arise - Quality-check collected data and perform signal preprocessing Participant-facing track: - Monitor the execution of data collection and provide participant support - Ensure privacy, ethical, and regulatory compliance *Experience* - Prior hands-on experience acquiring EEG and/or EMG data. This is non-negotiable: we need someone who has already sat with participants, placed electrodes, monitored signal quality in real time, and troubleshot acquisition problems as they happen. - Familiarity with the ethical and regulatory aspects of human-subjects research (informed consent, ethics-committee procedures) - Good communication skills and fluency in English *Engineering track:* - MSc or (preferred) PhD in Biomedical Engineering, Computer Science, Computational Neuroscience, or a related field - Experience working with the APIs provided alongside recording hardware (e.g., BrainVision, Biosemi, ANT, OpenBCI, or similar) - Strong Python skills, with the ability to build and maintain acquisition pipelines in code - Comfort with scripting, reading hardware documentation, and debugging and troubleshooting an acquisition setup *Participant-facing track:* - MSc in Medicine, Psychology, Biology, or a related field; the key qualification is hands-on, research-grade data collection - Exceptional communication skills, empathy, and the ability to design comfortable, suitable experimental environments - Experience managing scheduling, communication, and the overall participant experience - Basic familiarity with programming fundamentals and core AI concepts—enough to answer participants' questions about what a study involves *Compensation* Gross annual salary (RAL) of €35k–€50k for full-time, determined by your job-related skills, experience, and relevant education or training. *Position* Full-time or part-time (20–40h/week), on-site in Rome, Italy. Matteo Ferrante, Lead AI scientist at Tether Evo & CEO of Silenzio SRL.

Aug. 24, 2026

Job advertisement: Full professor in “Intelligence in Biological and Artificial Systems” (Osnabrück, Germany)

by Prof. Dr. Tim Kietzmann

Dear all, We are hiring a full professor in "Intelligence in Biological and Artificial Systems" at the institute of Cognitive Science in Osnabrück - Germany's first and largest cognitive science program. Please forward this information to any suitable candidates, and reach out if you have any questions. The call is published here: https://www.uni-osnabrueck.de/en/university/working-at-osnabrueck-universit… Some more information is provided here: https://www.linkedin.com/feed/update/urn:li:activity:7497392412361711618/ Best wishes Tim __________________________________ Prof. Dr. rer. nat. Tim C Kietzmann Professor for Machine Learning Institute of Cognitive Science Osnabrück University Osnabrück, Germany Web: https://www.kietzmannlab.org Email: tim.kietzmann(a)uni-osnabrueck.de Twitter: @TimKietzmann

Aug. 24, 2026

Postdoc studying episodic memory sampling in Spain

by Raphael Samuel Matthew Kaplan

The Universitat Jaume I's Decision & Memory group in Castelló de la Plana, Spain led by Prof. Raphael Kaplan is recruiting a junior postdoctoral researcher(<2 yrs since completing their PhD) to study how the human brain samples different event details/memories when imagining novel scenarios. The candidate will also test if episodic sampling processes can be optimized for learning interventions. Working with Prof. Kaplan and their team, the candidate will be expected to help collect and analyze behavioral, fMRI, and/or iEEG experimental data that test these questions. In parallel, the empirical results will be used to inform quantitative models investigating the same processes in collaboration with other leading international laboratories. The postdoctoral position involves training in behavioral/neuroimaging experimental design, behavioral and neuroimaging analysis, computational modeling, machine learning, manuscript preparation, and grant writing within a highly interdisciplinary research environment. Prof. Kaplan has an extensive international record of mentorship where they have incorporated career development opportunities both inside(e.g., fellowship writing, PhD/MSc trainee supervision, teaching) and outside of academia(e.g., big data analysis, clinical translation, public sector, user interface(UX) development) for their trainees. In exceptional cases, more senior postdoctoral candidates with an extensive CV and publication record studying related questions will be considered for a position. Required Skills: -Have a PhD in Experimental Psychology, Neuroscience, Cognitive Science, Engineering. or related field -Experience analyzing fMRI, intracranial EEG, or model-informed behavioral data. -Be able to independently carry out research within defined project objectives -Be capable of critical analysis, evaluation, and synthesis of new and complex ideas -Be able to communicate and publish research results effectively to colleagues and broader audiences in English. -Be able to work collaboratively in interdisciplinary research environments -Have good programming skills (e.g., Python) and experience with scientific computing tools Desired skills: -Recently received their PhD(after January 1st, 2025) -First author publications in established cognitive science and neuroscience journals. -Experience designing and publishing memory, learning, or decision making behavioral/neuroimaging research. -Strong quantitative and statistical background -Proficiency speaking Spanish and/or Catalan/Valencian Application details To apply for the position, interested candidates should send a 1-2 paragraph cover letter explaining why they're suited for the position along with a CV including name and contact info for 3 references to Prof. Kaplan at *kaplan(a)uji.es <kaplan(a)uji.es>* by September 15th. Potential candidates should contact Prof. Kaplan if they have any questions or need further information. *Type of contract/Duration of Contract*: Temporary, 2 years(potentially renewable) *Job Status:* Full-time, in office *Hours per week:* 35 *Starting date:* Flexible, ideally between December 2026-March 2027 *Application deadline: *September 15, 2026 *Salary: *30,000€-32,000€/year gross Recent relevant work by our group includes: Group website <https://www.uji.es/serveis/ocit/base/grupsinvestigacio/detall/?urlRedirect=…> Esposito, M., Abdul, L. S., Ghouse, A., Rodríguez Aramendía, M., & Kaplan, R. (2025). Flexible hippocampal representation of abstract boundaries supports memory-guided choice. Nature communications, 16(1), 2377. Rodríguez Aramendía, M., Esposito, M., & Kaplan, R. (2025). Social knowledge about others is anchored to self-knowledge in the hippocampal formation. PLoS Biology, 23(4), e3003050. Ghouse, A., & Kaplan, R. (2026). The influence of social content on episodic memory retrieval. Learning & Memory, 33(2-3), a054180 Ghouse, A., & Kaplan, R. (2025). The Relative Contributions of Traits and Contexts on Social Network Learning. Open Mind, 9, 1506–1527. -- Raphael Kaplan, PhD Associate Professor/Profesor Titular de Universidad(TU) Departament de Psicologia Bàsica, Clínica i Psicobiologia Universitat Jaume I kaplan(a)uji.es

Aug. 24, 2026

IOSP 2026 in Leiden: build a community-owned open science system

by Jonathan Starr

The Institute of Open Science Practices <https://iosp.science/> is hosting its 2026 workshops in Leiden from October 12 to 15, and we'd like you in the room. *It's free to attend.* Across the two main working days, the event will establish a participant-owned data storage consortium, publish datasets, code, and knowledge objects to it, create our own algorithms that assess the trust and value of what's published, and assemble community-owned collaboratives that route funding based on their interpretation of that analysis. The result will be a fully functional open science system, owned by the community that builds it, to test, build on, and iterate over the coming months and years. The pieces of open science already exist. It's time they were woven into a coherent system. You can already see the emerging data network here: https://www.iosp.science/datanetwork And the full workshop line-up is here: https://iosp.science/workshops Four ways to participate: 1. *Register.* The room holds 100 people, and last year 425 registered for an 80-person room, so a registration isn't yet a seat and we confirm by email. The form asks whether you'd need travel support; say so if you would. https://www.iosp.science/?signup=participant 2. *Contribute to the community track.* It runs alongside the main track on both working days and is an open space for talks, workshops, panels, and discussions around the four themes. https://www.iosp.science/submit-community-session 3. *Building a tool? Submit it to the showcase.* We'll stress-test it and build on it in Leiden. https://www.iosp.science/?signup=showcase 4. *Join the resilient data workshop.* The workshop that opens IOSP 2026 has you stand up an IPFS node and join a member-owned resilient data consortium. Your node will run either on your own laptop or on a Raspberry Pi kit you take home. There are only 20 seats and 10 take-home Raspberry Pi kits. Earlier sign-ups get first consideration if it fills. Signing up for this workshop also registers you for IOSP 2026. https://www.iosp.science/resilient-data-signup And finally, spread the word. Forward this, post the community-track call, or point a builder at the workshop or showcase. *Hope to see you in Leiden!* Jon, Ellie, and the IOSP organizing team *P.S.* The resilient data consortium needs data worth keeping. If you know a public dataset that could vanish—a shuttered project's archive, a retiring server, data whose funding ended—recommend it and we'll consider adding it to the network. Recommend a dataset: https://www.iosp.science/resilient-data-signup See what the network holds now: https://www.iosp.science/datanetwork

Aug. 21, 2026

Tenure-Track Assistant Professor in Psychological Science and Neuroscience

by Yuqing Zhu

Dear colleagues, The Psychological Science and Neuroscience departments at Pomona College in Claremont, CA, USA are seeking candidates with equal dedication to teaching and research in human neuroscience. The successful candidate will teach two courses per semester and have a productive research program involving undergraduate students, where they will examine the neural mechanisms of psychological phenomena. Computational methods are very welcome. Pomona College is a selective liberal arts college with close relationships between undergraduate students and faculty. If you have a passion for student mentorship and inclusive excellence in teaching, this would be a great fit for you. Please see the job ad here: https://academicjobsonline.org/ajo/jobs/32248. The position begins July 2027. Applications will be reviewed beginning October 1, 2026. Thank you for your consideration, Yuqing *** Yuqing Zhu, PhD (she/her) Assistant Professor of Neuroscience Pomona College | Claremont, CA 91711 Lincoln 3109 | Lab Website<https://zhulab.sites.pomona.edu/>

Aug. 19, 2026