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https://www.academictransfer.com/en/jobs/349061/two-phd-candidates-in-radiology… Requirements Specific Requirements You are highly motivated and driven to do research and you are eager to learn and
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.). Experience with collecting and processing experimental data of human movement. A deep curiosity for how biological systems and structures function. Good written and oral communication skills in English. The
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environment interventions. Developing a decision support system for municipalities to integrate health considerations into spatial planning policies. Would you like to learn more about what it’s like to pursue
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Science, Data Science, Artificial Intelligence or a related technical field. Experience and knowledgeable in AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven approaches
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Professor in Evolutionary Biophysics) Prof Dr Marcos Guimaraes (Associate Professor in Optospintronics) Project description: How do insects see the world? And what can we learn from animal eyes to develop new
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(preferably Python) and knowledge of and experience with the design and implementation of machine learning models A background in geospatial modelling, spatial statistics and machine/deep learning The ability
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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into spatial planning policies. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . Profile You should hold a Master's
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, Data Science, or a related field. Strong background in Natural Language Processing (NLP), Machine Learning, or Explainable AI (XAI); Experience with deep learning frameworks (e.g., PyTorch, TensorFlow
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, accelerometers, etc. - Proficient programming skills in Matlab/Python/LabVIEW, with an added advantage of specific experience in popular deep learning frameworks like PyTorch and TensorFlow. - Demonstrated