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Job description PhD position in computational neuroscience - Deep reinforcement learning closed-loop control for the treatment of epilepsy As part of the highly prestigious ERC Starting Grant
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of scripts and workflows to automatically identify type material on platforms such as GBIF (Global Biodiversity Information Facility); Linking specimens to original descriptions (protologues) via TreatmentBank
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Job description Short job description We are seeking a highly motivated and talented PhD researcher in the field of system identification and control engineering for mechanical/mechatronic systems
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full-time position as a doctoral fellow for an initial period of 11 months. This position is not automatically renewable: candidates are expected to apply in 2026 for a PhD Fellowship Strategic Basic
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nematode community to N mineralization and N2O emissions in realistic soil conditions. In this project, we will set up unique multitrophic experiments controlling for the presence of specific trophic groups
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closed-loop control. The technology, developed through detailed computer simulations, will be validated with preclinical experiments. The candidate will be part of a multidisciplinary team working towards
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gap by (a) implementing a large randomized controlled trial, and (b) involving stakeholders (adolescents, teachers, parents, organizations) via focus group interviews. In a first phase, we will collect
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disciplines: computer science/engineering or biomedical engineering. You have an excellent academic record of accomplishment. In particular, you have a good command of, and a strong interest in, computer
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Engineering, or equivalent. Candidates with background in operations research, systems engineering, control and optimization or in a closely related domain are strongly encouraged to apply. We offer a pleasant
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for a m/f/x PhD Student – Subject: Quality Issues in cell and gene therapies YOUR JOB Development and validation of quality control assays for ATMP characterisation Design, optimization and validation