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Researcher (R1) Application Deadline 8 May 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework
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, and/or machine learning. Preferably you finished a master in Computer Science, (Applied) Mathematics or related masters. Expertise in the field of visualization or visual analytics. You have good
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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degree in AI, Computing Science, Mathematics, or Data Science. Strong coding, communication and organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch
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of the Quantum & Computer Engineering (QCE) department is looking for a highly motivated PhD candidate who is eager to work on AI based solutions for predictive inteligence for MRI scanning. The candidate will
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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discipline. Experience with deep learning framework PyTorch or similar. Strong background in machine learning, image or signal processing. Knowledge of SotA models for multi-modality and scene understanding
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related discipline. A solid background in de novo protein design, protein structure prediction (Rosetta, AlphaFold, …), protein expression, structure elucidation, machine learning, C/C++ and/or Python with
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knowledge of and/or experience with validation of prediction models (regression or supervised machine learning), health technology assessment, decision curve analysis, and/or value-of-information analysis
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organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with