866 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions in Sweden
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Field
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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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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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also committed to building a safe and positive
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: October 2026 Full call details, eligibility criteria, application templates, and a matchmaking platform for identifying potential supervisors are available at: https://www.scilifelab.se/data-driven/ddls
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. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create
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of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. Your work duties will
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Website https://umustipendie.varbi.com/en/what:job/jobID:887298/type:job/where:39/apply… Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent Research FieldMedical sciencesYears
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project