24 parallel-computing-numerical-methods-"Multiple" PhD positions at Umeå University in Sweden
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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to develop novel machine learning methods to improve malware detection. The doctoral student position is offered within a research project financed by the Wallenberg AI, Autonomous Systems and Software Program
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educational programs in Computing Science, we are now seeking a PhD student with focus on Software Lifecycle Security. The Department of Computing Science has been growing rapidly in recent years, with a focus
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the flexibility of neural methods. If successful, the work has the potential to advance applications such as automated theorem proving, knowledge-graph inference, and causal analysis. The Department of Computing
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experience or knowledge in one or more of the following areas are also a merit: Space physics Plasma physics Computational physics Applied mathematics and modelling Numerical methods for partial differential
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orientation, quantitative approaches and survey analyses may also be relevant alongside qualitative methods. The employment Positions as doctoral students in the doctoral program amount to four years of full
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science (DDLS) uses data, computational methods, and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
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redefinition. Architectural discourse has often relied on standardized bodily models that mask the diversity of lived, gendered, and capacitated experiences. In response, this project explores how a multiplicity
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at the Faculty of Medicine are enrolled in the faculty-wide doctoral training programme. The programme comprises 25 credits and is offered in two study tracks: 25 credits across 8 semesters (4 years) or across 12