866 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions in Sweden
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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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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testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
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) and Machine Learning/NLP (Natural Language Processing) to capture both the network embeddedness and the qualitative B2B relationship features of supply chains. The project identifies key bottlenecks
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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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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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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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a strong constellation of both traditional applied biostatistics and expertise in artificial intelligence and machine learning, which is undergoing rapid development. The clinical activities
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link