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Specific Requirements Your are an independent, highly motivated researcher holding an MSc or MEng degree in biomedical engineering, nanobiology, medical informatics, clinical/biomedical technology, computer
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completed or near-completed MSc degree in Artificial Intelligence, Computational Linguistics, GeoInformatics, Geography, Geoscience, or a related field; experience with natural language processing (NLP
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meetings; participate in the Faculty of Science PhD training program; assist in teaching Bachelor and Master’s students; co-supervise and interact with junior scientists (technicians, MSc/BSc students). What
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interact with junior scientists (technicians, MSc/BSc students). What do you have to offer? You are excited about science and have a particular interest in, and preferably proven knowledge of depression
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-of-the art analysis of spatio-temporal and ecological data; Collaboration with researchers and (BSc/MSc) students from a variety of disciplinary backgrounds; This is a fixed-term position of 18 months (1.0 fte
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language
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criteria: a MSc degree in (molecular) biology, or a related discipline (obtained, or expected in the near future); demonstrable experience with basic molecular biology techniques; affinity for (or ideally
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closely with the other GenAIDE fellows and industrial partners; complete planned secondments; Contribute to the NACO research cluster (naco.liacs.nl); Selection Criteria MSc (or equivalent) in
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of Wageningen University & Research or external knowledge partners. Your qualities You are a: Strong Researcher: PhD or MSc in economics, business administration, or an agronomic discipline with an economic focus
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the BSc and MSc programs of the ENR Group; and actively contributing to a dynamic, inclusive, and collaborative research culture within the research group. You will work here The research is embedded within