We have a postdoc position at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging to fill this summer. The eligible candidate should have a strong background in fMRI and decision making. They will join the developmental computational psychiatry group, working on innovative topics, such as structure learning, complex decision making and mental health. The focus will be on conducting fMRI research with the possibility to do computational modelling.

The eligible candidate should have a strong background in fMRI and decision making. He will join the developmental computational psychiatry group, working on innovative topics, such as structure learning, complex decision making and mental health. The focus will be on conducting fMRI research with the possibility to do computational modelling.

We are offering a fully funded PhD opportunity to examine the interplay between attention and decision-making in complex, naturalistic tasks using advanced electro-/magnetoencephalography (E/MEG) techniques. Strong quantitative skills will be advantageous for this project. The project will be co-supervised by Dr. Konstantinos Tsetsos (University of Bristol) and Professor Anina Rich (Macquarie University). The selected student will join a unique PhD cohort, as part of a cotutelle graduate program between the University of Bristol and Macquarie University.

We are looking for a highly motivated researcher to join our group in interdisciplinary projects that focus on the development of computational models to understand how linguistic information is represented in the human brain during language comprehension. Computational encoding models in combination with deep learning-based machine learning techniques will be developed, compared, and applied to identify linguistic representations in the brain across languages.

A fixed-term research position is open for a post-doc, or for a PhD student nearing the end of his doctoral program. The goal of the research is to study hybrid collective intelligence systems for decision support in complex open-ended problems. It involves the design and implementation of a hybrid collective intelligence system to exploit the interaction between human experts and artificial agents based on knowledge graphs and ontologies for knowledge representation, integration and reasoning.

The Department of Engineering Mathematics at the University of Bristol is seeking an outstanding candidate to fill the role of Professor in Artificial Intelligence. You will have the opportunity to provide visionary leadership to the department and its staff, students, & partners, helping to strengthen and further develop our already impressive research and teaching programs in AI. Our Intelligent Systems Group supports the Faculty of Engineering's AI/Data Science Theme, fostering an inclusive environment for all.

We are looking for an excellent candidate with a master’s degree in MSc in Artificial Intelligence, Computer Science, Mathematics, Statistics, or a closely related field to join a project focused on developing an advanced transparent machine learning framework with application on movement behavioural analysis. Smartwatches and other wearable technologies allow us to continuously collect data on our daily movement behaviour patterns. We would like to understand how machine learning techniques can be used to learn causal effects from time-series data to identify and recommend effective changes in daily activities (i.e., possible behavioural interventions) that are expected to result in concrete health improvements (e.g., improving cardiorespiratory fitness). This research, at the intersection of machine learning and causality, aims to develop algorithms for finding causal relations between behavioural indicators learned from the time series data and associated health-outcomes.

We are seeking a motivated postdoctoral researcher to work on an interdisciplinary project at the intersection of deep learning and comparative politics. The candidate will work in the Human-Centered Machine Learning (HuMaLearn) team of Prof. Benoît Frénay and the Belgian and Comparative Politics team of Prof. Jérémy Dodeigne. The goal will be to develop new deep learning methodologies to analyse large corpuses of archive videos that picture political debates. We specifically aim to detect emotions, body language, movements, attitudes, etc. This project is linked to the ERC POLSTYLE project that Jérémy Dodeigne recently obtained, guaranteeing a stimulating research environment. The HuMaLearn team gathers about ten researchers, many of them being actively working in deep learning, but not only and with a keen openness to interdisciplinarity.

We have a position for a postdoctoral research associate to work on NAS and AutoML with Dr Elliot J. Crowley and the Bayesian and Neural Systems Group. The successful applicant will be based in the School of Engineering at the University of Edinburgh, and will have opportunities for collaboration within and outside of the school e.g. with colleagues in the Institute for Digital Communications and the Bayesian and Neural Systems Group. This position is funded for 24 months (provisional start date: November 2023) and the salary is UE07 £36,333 - £43,155 Per Annum.

The postdoctoral researcher will work on an interdisciplinary project at the intersection of deep learning and comparative politics. The candidate will work in the Human-Centered Machine Learning (HuMaLearn) team of Prof. Benoît Frénay and the Belgian and Comparative Politics team of Prof. Jérémy Dodeigne. The goal will be to develop new deep learning methodologies to analyse large corpuses of archive videos that picture political debates. We specifically aim to detect emotions, body language, movements, attitudes, etc. This project is linked to the ERC POLSTYLE project that Jérémy Dodeigne recently obtained, guaranteeing a stimulating research environment.

We are looking for highly motivated researchers to join our group in interdisciplinary projects that focus on the development of computational models to understand how linguistic information is represented in the human brain. Computational encoding models in combination with deep learning-based machine learning techniques will be developed, compared, and applied to identify linguistic representations in the brain. The projects are conducted in collaboration with UC Berkeley.

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.

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 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'.

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

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 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.

Two postdoctoral research positions and three PhD positions are available at the Sussex Centre for Consciousness Science (SCCS). The postdoc positions are funded for 2 years with a possible extension for another 2, starting as soon as suitable candidates are identified. The PhD positions are fully funded for 3.5 years, starting in September 2024, with an earlier start being negotiable. The ERC-funded positions will focus on computational (neuro)phenomenology, exploring different applications of a predictive processing view of conscious perception. One of the ERC PhD positions will specifically focus on perceptual diversity, analyzing and extending the Perception Census project. The SCCS PhD position is flexible regarding project focus and supervisor, inviting proposals with a computational/informatics element.

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.

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.

The project will be examining sensory processing in infants born prematurely and later trajectories of neurodevelopment, using a variety of neurocognitive methods. Infants were recruited as neonates and the postholder will be leading and conducting the follow up visits (when the infant is 18 months). The post would suit someone who is interested in infant development, neurodevelopmental conditions and has experience with infant/toddler EEG and eye tracking.

We have an open position for a postdoctoral researcher with experience in brain-computer interfacing and artificial intelligence to further advance our new class of Brain-Artificial Intelligence (BAI) interfaces. A central part of your research would be to further develop our BAI for single-unit data recorded in language areas of a post-stroke aphasia patient, a project we carry out in close collaboration with the Translational NeuroTechnology Lab at TUM, headed by Simon Jacob.

The Georgetown University Neuroscience of Language Training Program is seeking outstanding postdoctoral fellows who wish to become the future leaders of our field. We aim to develop well-rounded scientists who have a broad perspective on basic and clinical neuroscience of language research, along with the skills and track-record to succeed in their chosen career path. We offer a rich training environment in the nation’s capital where fellows conduct innovative research under the guidance of 18 faculty members studying basic and clinical neuroscience of language, along with sensory, motor, and cognitive systems as they pertain to language and communication. Fellows can work with a single faculty member or across multiple labs, including partner labs at Children’s National Hospital and the George Washington University. Fellows can also participate in clinical experiences, community engagement activities, professional development training, journal clubs, and seminars to enrich their training. Appointments are funded at NIH NRSA stipend rates for two years, assuming fellows remain in good standing after the first year. Fellows also receive additional funds for training-related expenses, such as workshops, courses, conference travel, computers, peripherals, etc.

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.