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advanced biostatistics/machine learning analyses, but also with other types of analysis. The work involves supporting Swedish researchers under a “user fee-based” support model. The projects will differ in
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if you have worked with prediction models, machine learning or AI models and are familiar with blood cells such as neutrophils, leukocytes and platelets. Work experience in the area is meritorious. If you
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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Description of the workplace The position will be placed at the division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an
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, semiconductor technology and metrology that are part of the SWEET project. About us The position is hosted by the Microwave Electronics Laboratory at MC2 where the PhD student will have access to several
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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that enhance the quality and efficiency of forest management planning. The PhD student will combine remote sensing with machine learning to detect cultural remains, predict terrain accessibility, identify
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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fusion to address key environmental challenges. Strategically positioned to impact Earth observation science, we collaborate on satellite development, NewSpace technologies, and apply machine learning