We offer a postdoctoral researcher position within the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen, The Netherlands. The position is funded by an NWO Vidi project named “mechanistic machine learning: combining the explanatory power of dynamic models with the predictive power of machine learning“. Systems of Artificial Intelligence (AI) and Machine Learning (ML) gained a tremendous amount of interest in recent years, demonstrating great performance for a wide variety of tasks, but typically only if they are trained on huge amounts of data. Moreover, frequently no insight into the decision making is available or required. Experts desire to know how their data can inform them about the natural processes being measured. Therefore we develop transparent and interpretable model- and data-driven hybrid methods that are demonstrated for applications in medicine and engineering. As a postdoc, you will work together with Kerstin Bunte and her team within the Intelligent Systems group, as well as a network of interdisciplinary collaborators in the UK and Europe from various fields, such as Computer Science, Engineering and Applied Mathematics.

Become a postdoctoral researcher or PhD student at the Human-centric AI Centre (HAI) at the University of Technology Sydney, Australia and work in frontier research in the areas of deep machine learning, trusted AI, trustworthy human-autonomy teaming, natural BCIs, reliable GPT, extended reality and swarm intelligence. We are seeking applicants for PhD scholarships and postdoctoral research positions with prior experience and skills in some of the following areas: machine learning fundamentals and generative models, deep learning optimisation and reinforcement learning, brain-computer interfaces, drones and robotics, trusted AI, extended reality.

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.

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.

Looking for a postdoctoral researcher to work as part of the Melbourne ARC Hub for Digital Bioprocess Development. This 3-year position will examine how relatively sparse high-quality data can be supplemented with lower quality data to enable ‘multi-fidelity’ optimisation for improved decision support for bioprocesses.

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.

We are looking for a postdoctoral researcher to develop new machine learning approaches for the analysis of large-scale extracellular recordings. The position is part of a wider effort to enable new discoveries with state-of-the-art electrode arrays and recording devices, and jointly supervised by Matthias Hennig and Matt Nolan. It offers a great opportunity to work with theoretical and experimental neuroscientists innovating open source tools and software for systems neuroscience.

The hired postdoctoral researcher will mainly work on WP2, i.e., on the development of new formalisms and methods to apply to higher order interaction patterns identified in the data analyzed in WP1. The project aims to build a theoretical and data analysis framework to demonstrate the role of higher-order interactions (HOIs) in human brain networks supporting causal learning. The Hinteract project includes three scientific work packages (WPs): WP1 focuses on developing an informational theoretical approach to infer task-related HOIs from neural time series and characterizing HOIs supporting causal learning using MEG and SEEG data. WP2 involves developing a network science formalism to analyze the structure and dynamics of functional HOIs patterns and characterizing the hierarchical organization of learning-related HOIs. WP3 is about compiling and sharing neuroinformatics tools developed in the project and making them interoperable with the EBRAINS infrastructure.

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.

We are looking to hire a highly motivated and driven postdoctoral researcher to understand human cooperation & competition using virtual reality. This ambitious project combines concepts from behavioural game theory and theory of mind in an existing VR setup, and is supported by a dedicated VR developer. The goal of the position is to understand human cooperation in dangerous situations. The role includes conceptual design of classical game-theoretic dilemmata in naturalistic VR scenarios with experimentally controlled non-verbal information channels, conducting and analysing experiments using motion capture data and an established R package (https://github.com/bachlab/vrthreat), and publication of research and development results.

The Pennsylvania State University is seeking an outstanding postdoctoral researcher to join the Intelligent Information Systems Laboratory at the College of Information Sciences and Technology. The position is available immediately or starting in Spring 2025. The researcher will be mentored for a successful transition to a faculty or scientist position in academia or a leading research laboratory as many of our previous postdoctoral fellows. You will be involved in leading and assisting in proposal preparation, research execution, and mentoring students on a project involving the use of AI in wildlife conservation. In addition to the wildlife conservation project, the postdoctoral fellow and the faculty mentors may identify and scope other areas of research to pursue. The position fully focuses on research with no expectation of teaching. However, should the scholar want to teach, arrangements can be made to build teaching experience. The objective of this position is to enhance the researcher’s skills and record for a placement in a leading university or research laboratory at the end of the post-doctoral position.

We invite applications for an enthusiastic postdoctoral researcher in the area of computational neuroscience or systems biology. A new collaborative project with Kyushu U has been launched to elucidate biochemical signaling involved in the development of the olfactory system. We are working on a project to simulate how neural circuits in the brain acquire function through development. As an example, we are focusing on the process of mitral cell dendritic pruning that leads to the acquisition of odor selectivity (Fujimoto 2023, Dev Cell 58, 1221–1236). This process is governed by the coupling of biochemical signaling of small G proteins and neuronal electrical activity. In addition, the neural circuit simulation will be performed to elucidate the emergent process of odor information processing. The NEURON simulator or other platform simulators will be useful for this project.

The CSNG Lab at the Faculty of Mathematics and Physics at the Charles University is seeking a highly motivated Postdoctoral Researcher to join our team to work on a digital twin model of the visual system. Funded by the JUNIOR Post-Doc Fund, this position offers an exciting opportunity to conduct cutting-edge research at the intersection of systems neuroscience, computational modeling, and AI. The project involves developing novel modular, multi-layer recurrent neural network (RNN) architectures that directly mirror the architecture of the primary visual cortex. Our models will establish a one-to-one mapping between individual neurons at different stages of the visual pathway and their artificial counterparts. They will explicitly incorporate functionally specific lateral recurrent interactions, excitatory and inhibitory neuronal classes, complex single-neuron transfer functions with adaptive mechanisms, synaptic depression, and others. We will first train our new RNNs on synthetic data generated by a state-of-the-art biologically realistic recurrent spiking model of the primary visual cortex developed in our group. After establishing the proof-of-concept on the synthetic data, we will translate our models to publicly available mouse and macaque data, as well as additional data from our experimental collaborators.

In this webinar, Dr Ye Tian and A/Prof Andrew Zalesky will present new research on mapping the functional architecture of the human subcortex. They used 3T and 7T functional MRI from more than 1000 people to map one of the most detailed functional atlases of the human subcortex to date. Comprising four hierarchical scales, the new atlas reveals the complex topographic organisation of the subcortex, which dynamically adapts to changing cognitive demands. The atlas enables whole-brain mapping of connectomes and has been used to optimise targeting of deep brain stimulation. This joint work with Professors Michael Breakspear and Daniel Margulies was recently published in Nature Neuroscience. In the second part of the webinar, Dr Ye Tian will present her current research on the biological ageing of different body systems, including the human brain, in health and degenerative conditions. Conducted in more than 30,000 individuals, this research reveals associations between the biological ageing of different body systems. She will show the impact of lifestyle factors on ageing and how advanced ageing can predict the risk of mortality. Associate Professor Andrew Zalesky is a Principal Researcher with a joint appointment between the Faculties of Engineering and Medicine at The University of Melbourne. He currently holds a NHMRC Senior Research Fellowship and serves as Associate Editor for Brain Topography, Neuroimage Clinical and Network Neuroscience. Dr Zalesky is recognised for the novel tools that he has developed to analyse brain networks and their application to the study of neuropsychiatric disorders. Dr Ye Tian is a postdoctoral researcher at the Department of Psychiatry, University of Melbourne. She received her PhD from the University of Melbourne in 2020, during which she established the Melbourne Subcortex Atlas. Dr Tian is interested in understanding brain organisation and using brain imaging techniques to unveil neuropathology underpinning neuropsychiatric disorders.