218 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Sweden
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, regression models or machine learning. Applicants from clinical hepatology with experience in the above fields can also be interesting. You will work in an interdisciplinary and international research
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preparation (for example, questionnaires, interviews, etc) and processing (for example, machine learning etc) for the DSS, with related documentation. In OPTIX, contributing to the digital twin models
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Railway Engineering is seeking a motivated and collaborative postdoctoral researcher for a project on developing machine learning tools for pavement management. The project is conducted in collaboration
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willing and able to learn quickly within a collaborative and interdisciplinary team. Instructions on how to apply For more information and documents/templates/europass link, please visit https
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integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and present research results from the project on conferences. Collaboration with
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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for the responsible integration of AI in education. You will work in an interdisciplinary research environment spanning human-computer interaction, intelligent tutoring systems, learning analytics, and education, in
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opportunity to develop deep expertise in robotics, machine learning, and control. WASP is a major national initiative for strategically motivated basic research, education and faculty recruitment. It is by far
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research areas especially along two themes: “Platform security and application”s and “Machine learning and security/privacy ”. Our goal is to provide the environment for the successful candidate to mature
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look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems