278 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions in Sweden
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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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postdoctoral researcher with a focus on AI trustworthiness modeling on multimodal data and machine learning models. The Department of Computing Science has been growing rapidly in recent years, with a focus on
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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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conducted implementations of algorithms and simulations using contemporary GPU hardware, or Profound knowledge and experience of the DUNE software environment (https://dune-project.org/ ) (knowledge and
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, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice or other forms of appointment / assignment relevant
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students as well. For more information about the department or division visit: https://www.slu.se/en/about-slu/organisation/departments/department-of-plant-biology/ Read more about our benefits and working
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interest in research team-work Industrial Experience from relevant industries Experience in computer based engineering and/or model based systems engineering tools What you will do Participate as researcher
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Department of Clinical Microbiology The Dwibedi research group at the Department of Clinical Microbiology and the Laboratory for Molecular Infection Medicine Sweden (MIMS; https://www.mims.umu.se
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statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity, be process-oriented and able to work independently. Being able
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methods to rigorously assess the safety and effectiveness of medications in real-world patient populations. Defining individualized treatment strategies: Leveraging traditional and causal machine learning