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leveraging advanced computer vision and deep learning-based pose estimation from football match footage to analyze pre-injury biomechanical patterns and joint load dynamics. The research aims to create
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operation by nonspecialized personnel, and to allow automated interpretation. As a PhD student you will develop novel deep learning methods for identification of fetal growth abnormality from ultrasound
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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group
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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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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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(geometric deep learning, transformer-based approaches, ...) with a focus on protein-ligand interaction dynamics in collaboration with wet-lab researchers? If so, this fully funded PhD position might be
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neurocomputational models for real-world auditory scenes! Job Description As a PhD candidate in our research team, you will develop neurocomputational models that integrate deep neural networks with neuroscientific
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the accurate prediction of reaction enthalpies and activation free energies for all relevant intermediates. In this project, a deep learning and generative design toolchain will be developed resulting in an ML
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Your job Are you looking for a PhD position where you develop state-of-the-art machine learning methods for the life sciences (geometric deep learning, transformer-based approaches, ...) with a
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Interdisciplinary PhD position Young Academy Groningen 2025 (V25.0079) « Back to the overview Job description We are looking for talented students who wish to design their own PhD research project