The Gonçalves lab is a recently founded research group at the Neuro-Electronics Flanders (NERF), Belgium, co-affiliated with the VIB Center for AI & Computational Biology. We are currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning. In particular, we develop machine learning methods to derive mechanistic insights from neuroscience data and apply them to challenging neuroscience problems: from the retrieval of complex input-output functions of biophysically-detailed single neurons to the full characterisation of mechanisms of compensation for perturbations in neural circuits. We work in an interdisciplinary, collaborative, and supportive work environment, which emphasizes diversity and inclusion. NERF is a joint research initiative by imec, VIB and KU Leuven. We are looking for a PhD and a postdoc candidates interested in developing machine learning methods and applying them to neuroscience problems. There will be flexibility to customise the project and ample opportunities to collaborate with top experimental and theoretical partners locally and internationally. More details about the positions and the lab can be found at https://jobso.id/hz2b https://jobso.id/hz2e

(Senior) Lecturer / Asst Prof in Machine Learning: One more position to join our new Centre for AI Fundamentals with already 5+ new academics, plus many old-timers in ELLIS Unit Manchester, UoM branch of the Alan Turing Institute and in @idsai_uom. Now we have kick-started e.g. a strong presence in NeurIPS2022. PhD students: Looking for PhD students in Probabilistic Machine learning; especially welcoming Multi-Agent RL for Human-AI Teamwork, as some really excellent ones will soon graduate and move on. But I have a few other topics too. Research Software Engineer: Position designed to bring the best of permanent good job at an excellent Univ, and top-notch Machine Learning with #TuringAIFellows in the new Centre for AI Fundamentals. Centre Manager for the Centre for AI Fundamentals and ELLIS Unit Manchester, and Translational Research Manager: Positions will be open any day now.

Several PhD/Postdoc/Engineer positions available in Viktor Jirsa’s group at the Institut de Neurosciences des Systèmes (INS), in Marseille, southern France. Positions include: 1) Researcher Position: Virtual Brain Twins in Epilepsy, 2) Researcher Position: Virtual Brain Twins in Psychiatric Disorders, 3) Postdoctoral Researcher in Multiscale Model Building to Simulate DIGITAL TWIN Brain Models in EBRAINS, 4) Postdoctoral Researcher in Stimulation Model Building to Simulate DIGITAL TWIN Brain Models in EBRAINS, 5) Postdoctoral Researcher in Machine Learning for Large-Scale Brain Network Models, 6) Engineer in Probabilistic Machine Learning for Building Workflows to Operate DIGITAL TWIN Brain Models in EBRAINS.

Manchester: Postdoc in probabilistic machine learning and sustainability; collaboration with an outstanding sustainability team - Univ Manchester is top in the UK and Europe, and 3rd in the world in the QS World University Ranking for Sustainability. This position belongs to the European Lighthouse of AI for Sustainability ELIAS. Helsinki: Probabilistic modelling and Bayesian inference for Machine Learning, ML for drug design, synthetic biology and biodesign, with differential privacy, for personalized medicine, for next-generation distribution shifts, or for collaborative machine learning.

This PhD project will push the boundaries of Continual Reinforcement Learning by investigating how agents can continuously learn and adapt over time, how they can autonomously develop and flexibly apply an ever-expanding repertoire of skills across various tasks, and what representations allow them to do this efficiently. The project aims to create AI systems that can sustain autonomous learning and adaptation in ever-changing environments with limited computational resources. The selected candidate will master and contribute to techniques in deep reinforcement learning, incorporating principles from probabilistic machine learning, such as information theory, intrinsic motivation, and open-ended learning frameworks. The project may use computer games as benchmarking tools or apply findings to robotic systems, including manipulators, intelligent autonomous vehicles, and humanoid robots.

The Uncertainty in Artificial Intelligence (UAI) group is looking for a highly motivated and skilled PhD candidate to work in the area of probabilistic machine learning. The position is fully funded for a term of four years. The research direction will be determined together with the successful candidate and in line with the NWO Perspectief Project Personalised Care in Oncology (www.personalisedcareinoncology.nl). The research topics may include, but are not restricted to: Probabilistic graphical models (Markov, Bayesian, credal networks), Causality: Theory and application, Cautious AI, including imprecise probabilities, Robust stochastic processes, Tractable models and decision-making, Online/continual learning with evolving data.

Postdoc in Sample-Efficient Probabilistic Machine Learning at the Department of Computer Science, University of Helsinki. The position is full-time, funded for 2 years and will be filled as soon as possible, with a starting date in autumn or winter 2024.