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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project
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that you will help us to build the sustainable companies and societies of the future. The Machine Learning Group at Luleå University of Technology seeks a doctoral student in machine learning. We offer well
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, chemical engineering, or materials science, with demonstrated experience at the interface of machine learning and chemical or materials data. You have expertise with machine learning methods for scientific
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Research Council (NWO). Within our institute physicists, chemists, engineers, and other specialists work together in multidisciplinary teams to accelerate the transition to a sustainable society. DIFFER’s
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: At least an upper second-class degree (preferably MSc) in a Science or Technology discipline. Good working knowledge of machine learning and deep learning. Hands-on knowledge of Python or PyTorch
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devices for medical imaging and reaction monitoring, as well as for the development of sustainable photocatalysts. In this role you will develop machine learning (ML)-accelerated quantum mechanics in
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PhD Candidate in Exposomics, Machine Learning and Artificial Intelligence Faculty: Faculty of Veterinary Medicine Department: Department Population Health Sciences Hours per week: 36 to 40
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. PhD Candidate Neuroimaging in Epilepsy Our goal: to leverage advanced Magnetic Resonance Imaging (MRI) techniques (including functional MRI to assess brain network metrics and MR spectroscopy to measure
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | about 1 month ago
, startups and patient partners. Your Mission as PhD is to develop novel machine-learning methods to (1) detect small, clinically meaningful changes in joints, (2) enable robust longitudinal monitoring and