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to the fundamentals of spatiotemporal data science and machine learning using scripting languages. Supervise BSc and MSc thesis students conducting research in Geo-information Science. You will work here The research
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, Introduction to Python, making figures using GGplot2 and basic machine learning. These courses are offered to PhD candidates through the PhD Course Centre of the Graduate School of Life Sciences . In
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of machine-learning models capable of analysing the potential of selected antigens as potential vaccine candidate and/or diagnostic target. You will work here The research is embedded within Wageningen
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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teaching and student supervision activities in areas related to your expertise. What we ask of you Your experience and profile A PhD degree in AI (e.g., machine learning, natural language processing
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extensive knowledge on zooplankton imaging techniques ability to program and train machine learning models for automated image classification experience with shipborne campaigns and ready to join multi-week
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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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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. This PhD position focuses on the design of novel computer architectures to enable large AI models to run on embedded and edge systems under strict timing, energy, and memory constraints. Current solutions
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adaptation, synthetic data generation, and cross-modal learning to enable models that generalize across defect types and machine configurations. This ensures scalable, accurate defect detection even in low