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of receiving their PhD. In particular for this position, the following is required: PhD in data science, AI, computer science, machine learning, Earth system science, climate etc., with a thesis subject relevant
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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perception systems, using deep learning and simulation-to-real domain adaptation techniques. You will work with a multidisciplinary team, contributing to fundamental and applied research. Your role will
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the dispersion of these macroplastic items in these flow fields; comparing the results of the simulations to results from an experimental campaign of floating trackers; collaborating with a postdoc and two PhD
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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: https://rademaker.unige.ch/ The candidate · holds a PhD (or an equivalent degree) in Theoretical Quantum Matter Physics by the starting date; · has excellent spoken and written English
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Employment 0.8 FTE Gross monthly salary € 4,728 - € 6,433 Required background PhD Organizational unit Faculty of Social Sciences Application deadline 08 March 2026 Apply now Join an ongoing NWO Vici
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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on resilient 6G connectivity for mission-critical applications, and contribute to innovative European and Dutch national projects together with a team of talented PhD researchers? Information The future 6G
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collaborate with the Principal Investigator and help coordinate research with and supervise the research of two PhDs working on the project (one who focuses on Nigeria, and one who focuses on Mozambique