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Systems Immunology Lab (Prof. Kiavash Movahedi, VUB) have a vacancy for a full-time (100%) co-joint doctoral project to study tissue-resident macrophages in neurological disorders. This collaborative
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an interest in bridging rigorous theoretical insights with challenging real-world tasks. They will also explore reinforcement learning strategies to optimize decision-making policies in complex
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assessment based on electrochemical impedance spectroscopy complemented with microscopic studies. (4) to create a set of guidelines to better select corrosion resistant alloys for sCO2. (5) To investigate
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, with a potential second-year renewal, and will involve work on theoretical and empirical research related to behavioral economics, decision making, household finance, and health behaviors. The research
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leveraging visual perception of human actions, object properties, and scene context. It integrates machine learning tools, knowledge representation, and robot actions design to develop decision-making
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possible, or a combination of the two. Topics of interest on which we plan to work are decision support for the use of software protection tools (i.e., to decide which protections to apply where in a program
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committee: the first week of October 3) Interviews : October 16 & early November 4) Final decision: end of November 5) Feedback to all applicants: end of November Contact details for enquiries: Prof. Mathieu
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 5 days ago
29 Aug 2025 Job Information Organisation/Company Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID Department DRH Research Field Engineering » Civil engineering
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out wet lab work which will feed and support your in silico research, and will be supervised by Prof. Spits – an expert in aneuploidy in early development – and bioinformatician Prof. Olsen. You’ll have
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adaptive, automated decision-making tools (e.g., traffic signal control, human–vehicle coordination, logistics optimization, route planning) using reinforcement learning in dynamic environments. Explanation