Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

This project aims to explore the adaptation of large language models (LLMs), such as ChatGPT, to study their potential in understanding human language and identifying associated pathologies. By focusing on advanced neurocomputational models and the use of functional MRI, this work aims to decipher linguistic representations and their individual variations, particularly in pathological contexts such as dyslexia.

A fully funded 3-years PhD position (EU MSCA-COFUND program) is available at Aix-Marseille University (France) for motivated students interested in the behavioral, neurophysiological and computational investigation of multistable visual perception in healthy and pathological populations. The project is strongly cross-disciplinary, including psychophysical and oculomotor experiments as well as advanced computational modeling. It will also involve an international mobility at the University of Edinburgh (UK), as well as a collaboration with the psychiatry department of Lille Hospital (France).

There is an open postdoc position to work on a collaborative project with Rik Henson and Emily Holmes at the Emotional Cognition Lab at the University of Cambridge. This post will involve conducting advanced memory modelling.

The FOX team of the CRIStAL laboratory (UMR CNRS), Lille, France, and the PR team of the MIS Laboratory, Amiens, France, are looking to recruit a post-doc starting as soon as possible and a joint PhD student starting in October 2025 in the field of asynchronous computer vision from event cameras. The main objective is to develop new models of spiking neural networks (SNN) capable of directly processing visual information in the form of spike trains. The proposed models must be validated experimentally on dynamic vision databases, following standard protocols and best practices. The PhD candidate will be funded for 3 years (grant application pending) and is expected to defend his/her thesis and graduate by the end of the contract. The monthly gross salary is around 2000€, including benefits. The post-doc will be hired for 18 months starting from March 2025 (this is a fully-funded position). The monthly gross salary is around 2500-3000€, including benefits.

The School of Psychology at the University of East Anglia has two lecturer / assistant professor posts available. We welcome applications in all areas of neuroscience – come join our outstanding faculty! We have great resources here at UEA (fNIRS, EEG, MRI, TMS, virtual reality, EyeLink 1000+, Tobii eye-trackers, mobile eye-trackers), including the newly established UEA Wellcome-Wolfson Brain Imaging Centre.

The Faculty of Psychology and Educational Sciences of the University of Coimbra (FPCE-UC) Portugal invites applications from rising and aspiring leaders in Computational Cognitive Neuroscience for 1 Assistant Professor position in Computational Cognitive Neuroscience. These positions are part of a transformative ERA Chair grant CogBooster from the European Union to FPCE-UC led by Dr. Alfonso Caramazza. The goal of CogBooster is to implement strong and international lines of research in Cognitive Science/Neuroscience, so as to contribute to the ongoing renewal of the Psychological and Brain Sciences in Portugal over the next decade. The project has recently led to the appointment of Jorge Almeida, Jason Fischer and Joana Carvalho as tenured Professors, and Alfonso Caramazza as a Visiting Researcher at the University of Coimbra. The University of Coimbra is an equal opportunity/affirmative action employer and has a Gender Equality Plan in place. We are committed to fostering a diverse and inclusive academic global community at the University. We particularly encourage applications from women, and from under-represented groups in the University of Coimbra’s workforce and in the brain sciences.

The AI Department of the Donders Centre for Cognition (DCC), embedded in the Donders Institute for Brain, Cognition and Behaviour, and the School of Artificial Intelligence at Radboud University Nijmegen are looking for a researcher in reinforcement learning with an emphasis on safety and robustness, an interest in natural computing as well as in applications in neurotechnology and other domains such as robotics, healthcare and/or sustainability. You will be expected to perform top-quality research in (deep) reinforcement learning, actively contribute to the DBI2 consortium, interact and collaborate with other researchers and specialists in academia and/or industry, and be an inspiring member of our staff with excellent communication skills. You are also expected to engage with students through teaching and master projects not exceeding 20% of your time.

The PostDoctoral researcher will conduct research activities in modelling and simulation of reward-modulated prosocial behavior and decision-making. The position is part of a larger effort to uncover the computational and mechanistic bases of prosociality and empathy at the behavioral and circuit levels. The role involves working at the interface between experimental data (animal behavior and electrophysiology) and theoretical modelling, with an emphasis on Multi-Agent Reinforcement Learning and neural population dynamics.

The Centre for Artificial Intelligence and Neuroscience at University of Bonn is looking to recruit a postdoctoral fellow and a PhD student to undertake high quality research and produce high-impact publications in a collaborative research project investigating the mechanisms of human aversive learning (a pre-clinical model of anxiety disorders) in a big-data approach. The project is led by Prof Dominik Bach. The goal of the advertised positions is to (a) conduct an fMRI mega-analysis of multi-voxel threat representations, using existing data from the ENIGMA consortium, and (b) adapt and improve methods to infer threat learning from psychophysiological and behavioural data in fMRI and ambulatory settings. The position involves a close collaboration with the Department for Imaging Neuroscience (FIL) at UCL Queen Square Institute of Neurology, London, UK, where part of the team is based. The role includes implementing fMRI analysis pipelines in HALFpipe, coordination with participating sites to obtain and process data, mega-analysis of threat representation geometry, implementing and developing psychophysiology and behavioural analysis pipelines using PsPM/Matlab, CogLearn/VRthreat/R, and statistical modelling (e.g. Rstan), and publication of research and development results.

The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), hosted by the University of São Paulo (USP), Brazil, and funded by the São Paulo Research Foundation (FAPESP), is offering two post-doctoral fellowships for recent PhDs with outstanding research potential. The fellowship will involve collaborations with research teams and laboratories associated with NeuroMat, strictly related to ongoing research lines developed by NeuroMat. The project may be developed at the laboratories of USP, campuses of São Paulo or Ribeirão Preto, or at UNICAMP, Campinas, in person. We seek candidates capable of developing independent research in one of the research lines below. 1. Stochastic modeling of neurobiological data. Candidates must have a strong background in probability theory with emphasis on stochastic processes. 2. Development of new statistical methods for neurobiological data. Candidates must have a strong background in statistics and data analysis and knowledge of computer programming. 3. Acquisition, processing, and quantitative analysis of neurobiological data. Candidates must have a strong background in neuroscience with previous experience in neurophysiological data acquisition, processing and analysis, and knowledge of computer programming. 4. Instrumentation development associated with brain stimuli. Candidates must have a strong background in electronic instrumentation, robotics, programing, and safety in medical equipment. The fellowship is competitive at an international level, and fellows benefit from extra funds for travel and research expenses plus limited support for relocation expenses.

We are pleased to announce an opportunity for a tax-free fully funded PhD studentship - Multimodal AI-based Diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) - at Plymouth University, UK. This exciting project aims to transform ADHD diagnosis by developing a multimodal Artificial Intelligence (AI) framework that addresses the significant limitations of current, subjective diagnostic practices. Although AI is emerging in ADHD research, its integration into standard clinical practices remains minimal. This project seeks to enhance diagnostic accuracy through a sophisticated integration of AI-driven insights that complement existing approaches. Some basic questions (among others) that this project will try to explore are: How can machine learning and deep learning models be tailored to various data types like neuroimaging to uncover distinct ADHD diagnostic patterns? What methods can be used to analyse fMRI data to delineate active brain regions and their connections, and how can these findings be linked to ADHD behaviours and cognitive functions? How can we refine AI models to handle high data dimensionality and heterogeneity and enhance decision-making transparency in clinical settings using Explainable AI (XAI) methods? What are the best practices to assess the robustness of AI models against the variability in ADHD diagnostic data? This ambitious project will allow the student to engage in a groundbreaking study at the intersection of AI, neuropsychiatry, and healthcare and gain experience in a highly collaborative environment supported by a strong supervisory team and international experts. The research leverages our team's extensive background in neuro-developmental disorders like Autism Spectrum Disorder (ASD), where we recently discussed important brain regions related to ASD diagnosis. This PhD opportunity offers a deep dive not only into the diagnosis of ADHD using explainable AI but also into other related co-occurring disorders like ASD, providing a holistic perspective on patient care and intervention strategies across the spectrum of these interrelated conditions.

We are pleased to announce an opportunity for a tax-free fully funded PhD studentship - Multimodal AI-based Diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) - at Plymouth University, UK. This exciting project aims to transform ADHD diagnosis by developing a multimodal Artificial Intelligence (AI) framework that addresses the significant limitations of current, subjective diagnostic practices. Although AI is emerging in ADHD research, its integration into standard clinical practices remains minimal. This project seeks to enhance diagnostic accuracy through a sophisticated integration of AI-driven insights that complement existing approaches. Some basic questions (among others) that this project will try to explore are: How can machine learning and deep learning models be tailored to various data types like neuroimaging to uncover distinct ADHD diagnostic patterns? What methods can be used to analyse fMRI data to delineate active brain regions and their connections, and how can these findings be linked to ADHD behaviours and cognitive functions? How can we refine AI models to handle high data dimensionality and heterogeneity and enhance decision-making transparency in clinical settings using Explainable AI (XAI) methods? What are the best practices to assess the robustness of AI models against the variability in ADHD diagnostic data? This ambitious project will allow the student to engage in a groundbreaking study at the intersection of AI, neuropsychiatry, and healthcare and gain experience in a highly collaborative environment supported by a strong supervisory team and international experts. The research leverages our team's extensive background in neuro-developmental disorders like Autism Spectrum Disorder (ASD), where we recently discussed important brain regions related to ASD diagnosis. This PhD opportunity offers a deep dive not only into the diagnosis of ADHD using explainable AI but also into other related co-occurring disorders like ASD, providing a holistic perspective on patient care and intervention strategies across the spectrum of these interrelated conditions.

I'm looking for postdocs who'd like to apply for the Connected Minds PDFs with me and collaborators to work on the following potential projects: 1. explainable neuroAI for ANN / SNN models of motor control 2. neuromorphic robotic control 3. neurorobotic artistic performance 4. whole brain motor control networks identified through MEG and inverse optimal control. More information about the 2-yr Connected Minds PDF application, including eligibility criteria can be found here: https://www.yorku.ca/research/connected-minds/postdoctoral-fellowships/. I will of course help assembling the advisory team, writing the research project description and provide general guidance for the application. Feel free to check out my lab's website <http://compneurosci.com/> and WIKI <http://compneurosci.com/wiki/index.php/Main_Page> to get a better sense of who we are and how we work...

Up to 6 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2025. 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 6 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.

We have an opening for a Tenure-Track Professorship in the field of Responsible Computing within the Faculty of Computer Science at the University of Vienna. We are seeking applicants with a strong background in Computer Science and an excellent research record in responsible computing, as evidenced by publications in relevant top venues (such as ACM CHI, ACM FAccT, ACM AIES, NeurIPS, ICML, AAAI, the International Journal of Human-Computer Studies, or the ACM Journal on Responsible Computing) and by successful acquisition of research grants.

The position focuses on translating AI-guided tools for understanding brain computations and predicting brain and mental health disorders.

The Max Planck School of Cognition together with the Berlin School of Mind and Brain at Humboldt University offers two full DAAD scholarships for research towards a PhD degree.

The School of Computer Science and Electronic Engineering is seeking to recruit a full-time Lecturer in Natural Language Processing to grow our AI research. The School is home to two established research centres with expertise in AI and Machine Learning: the Computer Science Research Centre and the Centre for Vision, Speech and Signal Processing (CVSSP). This post is aligned to the Nature Inspired Computer and Engineering group within Computer Science. This role encourages applicants from the areas of natural language processing including language modelling, language generation (machine translation/summarisation), explainability and reasoning in NLP, and/or aligned multimodal challenges for NLP (vision-language, audio-language, and so on) and we are particularly interested in candidates who enhance our current strengths and bring complementary areas of AI expertise. Surrey has an established international reputation in AI research, 1st in the UK for computer vision and top 10 for AI, computer vision, machine learning and natural language processing (CSRankings.org) and were 7th in the UK for REF2021 outputs in Computer Science research. Computer Science and CVSSP are at the core of the Surrey Institute for People-Centred AI (PAI), established in 2021 as a pan-University initiative which brings together leading AI research with cross-discipline expertise across health, social, behavioural, and engineering sciences, and business, law, and the creative arts to shape future AI to benefit people and society. PAI leads a portfolio of £100m in grant awards including major research activities in creative industries and healthcare, and two doctoral training programmes with funding for over 100 PhD researchers: the UKRI AI Centre for Doctoral Training in AI for Digital Media Inclusion, and the Leverhulme Trust Doctoral Training Network in AI-Enabled Digital Accessibility.

ELLIS Institute Finland is recruiting Principal Investigators (PIs) to lead research teams in AI, machine learning (ML) and related fields. This is a unique opportunity for researchers at all career stages to do work with global impact, in a research environment that is one of the best in the world today for AI and ML. The selected PIs will become Fellows or Scholars of the ELLIS Society, a distinction of high-caliber scientists advancing the fields of AI and ML. PIs in the ELLIS Institute will enjoy great academic freedom and will have access to considerable funding for personnel, equipment, and running costs. The positions are faculty roles on the tenure track at participating Finnish universities.

Postdoctoral Researcher for a 27-month contract as part of the 'The CirculaR Economy Buildings as Material Banks (REBUILD)' project. The role involves designing, implementing, and evaluating a toolkit to simulate the use of multiple building materials, assessing their economic and carbon emission impact. Expertise in optimisation methods to handle conflicting objectives is particularly valuable.

The Perception and Plasticity Group of Caspar Schwiedrzik at the DPZ is looking for an outstanding postdoc interested in studying the neural basis of high-dimensional category learning in vision. The project investigates neural mechanisms of category learning at the level of circuits and single cells, utilizing electrophysiology, functional magnetic resonance imaging, behavioral testing in humans and non-human primates, and computational modeling. It is funded by an ERC Consolidator Grant (Acronym DimLearn; “Flexible Dimensionality of Representational Spaces in Category Learning”). The postdoc’s project will focus on investigating the neural basis of visual category learning in macaque monkeys combining chronic multi-electrode electrophysiological recordings and electrical microstimulation. In addition, the postdoc will have the opportunity to cooperate with other lab members on parallel computational investigations using artificial neural networks as well as comparative research exploring the same questions in humans. The postdoc will play a key role in our research efforts in this area. The lab is located at Ruhr-University Bochum and the German Primate Center in Göttingen. At both locations, the lab is embedded into interdisciplinary research centers with international faculty and students pursuing cutting-edge research in cognitive and computational neuroscience. The main site for this part of the project will be Göttingen. The postdoc will have access to state-of-the-art electrophysiology, an imaging center with a dedicated 3T research scanner, and behavioral setups. The project will be conducted in close collaboration with the labs of Fabian Sinz, Alexander Gail, and Igor Kagan.

The successful candidates will join a dynamic interdisciplinary collaboration between A/Prof Mac Shine (Brain and Mind Centre), A/Prof Joseph Lizier (School of Computer Science) and Dr Ben Fulcher (School of Physics), within the University's Centre for Complex Systems, focused on advancing our understanding of brain function and cognition using cutting-edge computational and neuroimaging techniques at the intersection of network neuroscience, dynamical systems and information theory. The positions are funded by a grant from the Australian Research Council 'Evaluating the Network Neuroscience of Human Cognition to Improve AI'.

You will be working in the Pattern Analysis and Computer Vision (PAVIS) Research Line, in collaboration with the Rehab Technologies and EDPR units. The IIT teams are a multi-disciplinary and multi-cultural group where people with different backgrounds collaborate, each with their own expertise, to carry out research on Computer Vision, Rehabilitation Technologies and Artificial Intelligence. PAVIS Research Line is coordinated by Dr. Alessio Del Bue. PAVIS developed an intelligent sensor network infrastructure at the Center for Human Technologies to deploy, test, and validate human-centric AI approaches in collaboration with several IIT PIs. This infrastructure is used to deploy assistive AI technology, and it will be critical to integrating computational and robotics systems for social good and healthcare applications as part of IIT's Flagships program. Within the research team, your main responsibilities will be: Developing software for cutting edge interdisciplinary technology transfer projects in the area of health care, concretely, Intelligent and Interactive environments to assist frail patients; Collaborating closely with other research units and groups at IIT in multi-group collaborations involving advanced software architectures, machine learning and robotics (e.g. exoskeletons); Prototyping of Proof of Concepts, demonstrations, and use cases together with engineers and researchers with different backgrounds; Providing support on pre-clinical and clinical experiments with real patients; Providing support on the technical preparation of documentation (e.g. technical reports).

I have a PhD opening in deep learning for monitoring marine ecosystems. The research will be done in cooperation with the Institute of Marine Research in Norway.

Call for 5 open-rank positions at IT:U — a new public university just founded in Austria. One of the focuses is Theoretical Foundations of Data Science — engaging with areas such as mathematics of data science, statistical learning, or specific topics like topological data analysis and causality. The concept of “Data Science” here is very broadly defined. The positions are attractive, and include permanent (i.e. recurring) funding for a number of PhD students and post-docs, depending on rank.

Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.

Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain’s information coding via discrete voltage spikes. However, it remains unclear how both artificial and natural networks of spiking neurons can learn energy-efficient information processing strategies. Here we propose Predictive Coding Light (PCL), a recurrent hierarchical spiking neural network for unsupervised representation learning. In contrast to previous predictive coding approaches, PCL does not transmit prediction errors to higher processing stages. Instead, it suppresses the most predictable spikes and transmits a compressed representation of the input. Using only biologically plausible spike-timing based learning rules, PCL reproduces a wealth of findings on information processing in visual cortex and permits strong performance in downstream classification tasks. Overall, PCL offers a new approach to predictive coding and its implementation in natural and artificial spiking neural networks

I am hiring postdocs to my group in Helsinki, in combinations of the following: foundations of (probabilistic) machine learning, beyond current distribution shift models, AI-assistance with computationally rational user models, particularly attractive applications in synthetic biology and biodesign. FCAI is looking for Postdocs, Research fellows, and PhD students in Machine learning and AI. Finnish Center for Artificial Intelligence FCAI and ELLIS Unit Helsinki are looking for several postdocs, research fellows and PhD students to join us in creating new machine learning techniques – your work can be theoretical or applied, or both. We have opportunities in the following areas of research: Reinforcement learning, Probabilistic methods, Simulation-based inference, Privacy-preserving machine learning, Collaborative AI and human modeling, Machine learning for science.

Postdocs in Helsinki: Topic: combinations of the following: - foundations of (probabilistic) machine learning - beyond current distribution shift models - AI-assistance with computationally rational user models - particularly attractive applications in synthetic biology and biodesign. Postdoc or research fellow in Manchester, UK: Develop new principles and probabilistic machine learning methods for Advanced User Modelling, sequential decision making and Automatic Experimental Design, with and without a Human-in-the-Loop. PhD students in Manchester, UK. FCAI is looking for Postdocs, Research fellows, and PhD students in Machine learning and AI. Finnish Center for Artificial Intelligence FCAI and ELLIS Unit Helsinki are looking for several postdocs, research fellows and PhD students to join us in creating new machine learning techniques – your work can be theoretical or applied, or both. We have opportunities in the following areas of research: 1) Reinforcement learning 2) Probabilistic methods 3) Simulation-based inference 4) Privacy-preserving machine learning 5) Collaborative AI and human modeling 6) Machine learning for science.

AI.SG will be releasing the PhD fellowship call very soon. This competitive fellowship is for top AI students interested in doing a PhD at Singapore University of Technology and Design with excellent compensation. There will be a tight application window hence the advance notice. Postdoc fellowships are available for ASEAN nationals through the SASEAF fellowship, deadline 31 Jan.

Most code is now written as a collaboration between humans and code-assistive technologies, which are based on foundation models, trained on text and source code. How can we ensure that this collaboration is most effective? In this ambitious project, we will develop methods based on machine learning, cognitive science, and software engineering that improve the effectiveness of human-AI collaboration in the domain of code generation. An example of a concrete research question of interest is how to adapt the model output based on inferences about the user's cognitive state. We will also validate our developed methods via large-scale crowdsourced human experiments as well as in-person studies with a more focused population of programmers.

Exciting opportunity for early-stage researchers to join the TUAI (Towards an Understanding of Artificial Intelligence) project, a Marie Skłodowska-Curie Doctoral Network funded by the European Union’s Horizon Europe program. We are currently offering PhD positions aimed at fostering transparent, open, and explainable AI through innovative research. The TUAI project aims to bridge technical advancements in AI with societal needs, promoting ethical, responsible, and inclusive AI systems.

The Hertz Chair for Artificial Intelligence and Neuroscience at University of Bonn is looking to recruit a postdoctoral fellow or PhD student to undertake high quality research and produce high-impact publications in a collaborative research project investigating human escape using wearable magnetoencephalography with optically pumped magnometers (OPM). The goal of the advertised position is to understand the neural control of human escape decisions in an immersive virtual reality (VR) environment using an OPM-compatible HMD, in collaboration with the Wellcome Platform for Naturalistic Neuroimaging, which is part of the FIL at the UCL Queen Square Institute of Neurology, London, UK. The role includes conceptual design of naturalistic VR scenarios that allow MEG recordings, planning, conducting, and analysing MEG experiments, building robust pipelines for MEG analysis in naturalistic settings, and publication of research and development results.

The Hertz Chair for Artificial Intelligence and Neuroscience at University of Bonn is looking to recruit a postdoctoral fellow or PhD student to undertake high quality research and produce high-impact publications in a collaborative research project investigating human escape using wearable magnetoencephalography with optically pumped magnometers (OPM). The goal of the advertised position is to understand the neural control of human escape decisions in an immersive virtual reality (VR) environment using an OPM-compatible HMD, in collaboration with the Wellcome Platform for Naturalistic Neuroimaging, which is part of the FIL at the UCL Queen Square Institute of Neurology, London, UK. The role includes conceptual design of naturalistic VR scenarios that allow MEG recordings, planning, conducting, and analysing MEG experiments, building robust pipelines for MEG analysis in naturalistic settings, and publication of research and development results.

The Faculty of Computer Science at HSE University Moscow is looking for tenure-track assistant professor positions in various computer science areas. Successful candidates will conduct impactful research with institutional support. Positions typically begin in September 2025, with an initial three-year term.

The new research team NECTARINE at INRIA in Strasbourg / France aims to create a synergy between clinicians and mathematical researchers to develop new healthcare technologies. The team works on stochastic microscopic network models to describe macroscopic experimental data, such as behavior and/or encephalographic. They collaborate closely with clinicians and choose their research focus along the clinical applications. Major scientific objectives are stochastic multi-scale simulations and mean-field descriptions of neural activity on the macroscopic scale. Moreover, merging experimental data and numerical models by machine learning techniques is an additional objective. The team's clinical research focuses on neuromodulation of patients suffering from deficits in attention and temporal prediction. The team offers the possibility to apply for a permanent position as Chargé de Recherche (CR) or Directeur de Recherche (DR) in the research field of mathematical neuroscience with a strong focus on stochastic dynamics linking brain network modelling with experimental data.

We are looking for a new team member with the following profile: You have an open-minded and collaborative attitude towards doing groundbreaking digital humanities research; You have a firm grasp on computational methods and are willing to achieve proficiency in historical research methods; You have a Ph.D. degree in semantic web, digital humanities, language technology, or a related field by the starting date of the project; Your English is excellent and you have or are willing to obtain a working proficiency in Dutch. Why you should consider working with us: Location, location, location: Our offices are located in a historical building in downtown Amsterdam. Researchers work together in projects and a shared office space and can choose to spend part of their time at home. The team: We value a social, open and inquisitive, safe work environment where your input counts, not your job title, this means open conversations about pros and cons of a particular idea and approach based on content, not status. We also brew a mean cup of coffee and the office has a cooking club. Good to know: The Royal Netherlands Academy of Arts and Sciences is not an educational institution, this means that you can focus on building your research profile without a teaching load. We do work together with various Dutch universities so some teaching is an option. About the procedure: Apply by 10 January 2025 via https://vacatures.knaw.nl/job-invite/2438/. Please do not provide more information than what is requested (motivation letter, CV, 1-page research-statement and one illustrative publication). If the committee requires more information, they will ask. The hiring committee will review the applications and invite candidates for an online interview with an optional second interview. The first round of interviews will take place online on 22 January. Starting date & duration: the starting date is negotiable but the project team prefers to fill the vacancy sooner rather than later. The position is for three years.

The Faculty of Computer Science at UNamur has an open academic position in distributed systems. The Faculty is more than 50 years old and is located in Namur, an historical city at the center of Wallonia. We are looking for candidates that will create and contribute to collaborations in line with the Faculty's areas of interest (software engineering, data engineering, data science, artificial intelligence, security, formal methods, modeling...).

This project involves modelling the staggered development and the decline with age of spatial coding in the mammalian brain, as well as data analysis of single neuron recordings. The position is based at Newcastle University, UK, with a rotation in the lab of Prof. Colin Lever in Durham, UK. The project is fully funded for 4 years by the BBSRC. Both international and UK students can apply, and fees are covered.

The University of Bristol is pleased to offer a fully-funded PhD position to study the processing of traumatic memories during sleep using advanced machine learning techniques. The successful candidate will be supervised by an interdisciplinary team of experimental and computational neuroscientists, including Dr. Ross Purple, Dr. Sean Froudist-Walsh, and Dr. Eleonora Russo. This project will also involve collaboration with the Sant’Anna School of Advanced Studies in Pisa, Italy.

The International Max Planck Research School (IMPRS) for Language Sciences is offering two fully-funded PhD Fellowship for four years (2025-2029) with a preferred start-date in September or October, 2025. The goal of the scheme is to enable young researchers to pursue interdisciplinary research projects in the language sciences, supervised by leading scientists at the Max Planck Institute for Psycholinguistics and its partner institutes at the Radboud University -- the Centre for Language Studies and the Donders Institute for Brain, Cognition and Behaviour.

The Institute of Theoretical Computer Science at Graz University of Technology (Austria) has opened a Tenure Track Assistant Professor Position in the area of Machine Learning and Artificial Intelligence. The research focus will be on basic research in the overlapping field of sub-symbolic and symbolic AI within the prestigious Cluster of Excellence Bilateral AI.

We have are looking to fill a fully funded 3-year Ph.D. student position in the field of deep learning-based signal processing algorithms for speech enhancement and computational audition. The position is funded by the German research council (DFG) within the Collaborative Research Centre SFB 1330 “Hearing Acoustics” at the Department of Medical Physics and Acoustics, University of Oldenburg. Within project B3 of the research centre, the Computational Audition Group develops machine learning algorithms for signal processing of speech and audio data.

📢 Join the Lin Lab at Mount Sinai! We’re Hiring Postdocs, Research Assistants, and PhD Students! The Lin Lab, also known as the Bytes of Minds Lab, is on the lookout for driven researchers passionate about Computational Psychiatry and Neuro-AI. Directed by Dr. Baihan Lin (me!) and based at the Icahn School of Medicine at Mount Sinai, New York’s largest hospital network, our lab is uniquely positioned with access to vast data resources and a strong collaborative environment. We’re pushing the boundaries of mental health technology and brain-inspired AI to create intelligent systems that can transform healthcare and deepen our understanding of the mind. Why Join Us? 🍎 Cutting-edge Research: Tackle challenges in neuro-inspired AI, computational psychiatry, brain-computer interfaces, extended realities (XR), social media, wearables, and beyond. 🍎 Interdisciplinary Impact: Work at the intersection of advanced neuroscience, machine learning, and cognitive science to create adaptive AI systems, new tools for mental health, and next-gen neurotechnology. 🍎 Top-Tier Environment: Join Mount Sinai’s dynamic research community, within New York’s largest health system with the most diverse patient populations and a leading hub for AI in healthcare (ranked #1 by Nature). Whether you're a potential postdoc, PhD student, or someone looking for an interdisciplinary research experience, if you’re passionate about bridging the gap between bytes and minds, we want to hear from you! Learn more at linlab.org and apply by emailing me at baihan.lin@mssm.edu. Bytes of Minds Lab (Lin Lab) Departments of AI, Psychiatry, and Neuroscience Hasso Plattner Institute for Digital Health, Friedman Brain Institute, Center for Computational Psychiatry

A postdoctoral position is available in the Computational Neuroscience Unit (https://groups.oist.jp/cnu) of Prof. Erik De Schutter at the Okinawa Institute of Science and Technology for a researcher interested in modeling to help better understanding of cerebellar properties and function. Candidates should have good knowledge of cerebellar anatomy and physiology related to previous modeling work, and be open to an explorative approach. Depending on prior experience and interest the focus can be on modeling the cerebellum and its neurons and/or on analyzing experimental data obtained through collaboration. The postdoc will interact with other researchers and students in the lab who are working on cerebellar modeling projects. We offer attractive working conditions in an English language graduate university, located on a beautiful subtropical island. Starting date any time before end 2024. Send curriculum vitae, summary of research interests and experience, and the names of two referees to Prof. Erik De Schutter at erik@oist.jp