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application! We are seeking a highly motivated PhD student to join a research project at the forefront of battery diagnostics and modelling, that will help shape the future of battery technology by developing
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rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is characterized by close
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statistical machine learning models and methods, Bayesian learning, or an area related to those mentioned in Work Assignments is also strongly advantageous. Solid programming skills in Python. Experience with
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and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. STIMA is characterized by a modern view of the statistical subject, where probabilistic models
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-language-action models (VLA), specifically the handling of uncertainty in VLAs. VLAs have the potential to simplify system design in robotics and autonomous driving, both through verbal user interfaces, and
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postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and
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a modern view of the statistical subject, where probabilistic models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view of machine learning
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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
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, where AI models are trained without having all data in a single computer. This makes it possible to use larger datasets for training, without sending sensitive data between hospitals. The goal is to
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publish solid contributions at the best machine learning conferences. STIMA is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational