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(Groningen), and the UK. This post-doc project offers a unique opportunity to work in an international environment and to acquire valuable research experience for someone who has recently completed a PhD in
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within a few months from defending your PhD. You are familiar with Reinforcement Learning, Explainable Reinforcement Learning (XRL), fairness in Reinforcement Learning models. You have demonstrated
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develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques
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researchers writing PhD theses on ‘making’ in Roman literature, and two research assistants who support the team. Together, we work towards a new understanding of the ethics and aesthetics of making in
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researcher will work as part of a team which also includes the principal investigator, two junior researchers writing PhD theses on ‘making’ in Roman literature, and two research assistants who support the
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and various Nobel prize winners. Qualifications We are seeking a candidate with a PhD in Bioinformatics, Machine learning and AI-based statistics, Computational Biology, and expertise in Analytical
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PhD* in a topic such as animal acoustics, machine learning, quantitative ecology, quantitative biology, signal processing or similar. Evidence of the ability to conduct high-quality research and write
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for this position will have the following qualifications/qualities A PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in
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, data analysis, writing and publication) Support the setup and management of the overall project including data management and ethical clearance Be involved in the daily supervision of PhD students
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setting, alongside a postdoctoral and PhD researcher, to integrate models and data from different fields (e.g. economics, public health, environmental science). Specifically, you will: Further extend