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. Your competencies Prospective applicants should have the following qualifications: M.Sc. degree in wireless communications, communications engineering, computer engineering or similar; solid mathematical
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screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot
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interdisciplinary, applied research with expertise in visualization, design, computer graphics, and the learning sciences. The research nexus for the division is the Visualization Center C, a unique science center in
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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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Bård Halvorsen 1st September 2025 Languages English English English Digitalisation and Society PhD in Machine Learning for Critical Healthcare Apply for this job See advertisement About the position
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of good-quality data is typically limited for high-value critical assets. This PhD project will focus on developing, evaluating, and demonstrating physics-informed machine learning or domain knowledge
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agriculture and food security in Bangladesh”. This PhD project will co-create and co-design climate information services for short-to-long-term adaptation strategies for smallholder farmers to tackle weather
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sciences Economic and Administrative sciences Maritime sciences Social sciences and Humanities. The Faculty is also responsible for PhD programmes in computer technology, innovation and regional development
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., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students