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Mentor and Advise PhD thesis within the research group. Current topics include, reinforcement learning for tactile-aware manipulation skills, tactile sensing, mechanical intelligence for grasping, and
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify
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research appointment beginning July 1, 2026. Candidates are required to have received a PhD or equivalent in Mathematics or related field by the start of their appointment, and they may have up to three
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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and plasticity of circadian clock neurons in rodents and fruitflies. Applicants must have a PhD in Biology or Neuroscience and experience in molecular biology, electrophysiology and animal handling, as
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robotic arms and performing software and hardware integration Mentor and Advise PhD thesis within the research group. Current topics include, reinforcement learning for tactile-aware manipulation skills
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to bring to the lab. They will be expected to help teach other trainees rotating in the laboratory, including pulmonary and critical care fellows, medicine residents, PhD candidates, medical students, and
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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. Where to apply E-mail lorraine.dubuis@unige.ch Requirements Research FieldPsychological sciencesEducation LevelPhD or equivalent Skills/Qualifications Desired profile: PhD in psychology, neuroscience
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We invite applications for a postdoctoral researcher to join the UMLFF project at the University of Luxembourg. The project aims to develop the next generation of uncertainty-aware machine-learning