215 machine-learning-"https:" "https:" "https:" "https:" "https:" positions in Sweden
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, providing excellent opportunities for the prospective candidates to expand the professional network and acquire useful multidisciplinary skills and qualities. Please see our latest publication in Science
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software related to the medical field Experience of specific software and programming languages, specifically ones suitable for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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and expertise in brain imaging (MRI), image processing and machine learning. Coordinating projects within the research group, supervising students and writing applications are also included in the role
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(e.g., from the viewpoint of physics, chemistry, or mechanical engineering), programming, machine learning, or equipment automation (including microfluidic systems, robotics and remote sensing
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machine learning models in simple, standalone devices that are capable of advanced processing. Building on our work on solution-based neuromorphic classifiers (https://doi.org/10.1002/advs.202207023
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-disciplinary research at the intersection of artificial intelligence, robotics, machine learning, and human-robot interaction. Subject area The subject area for this position is Computer Science. Background
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electronic systems. You will also develop and teach courses in electronics design at the bachelor and master levels, and take part in the further evolution of the excellent and multi-faceted research and
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. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to