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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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multidisciplinary research and education environment that advances the state-of-the-art knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material
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focuses on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally
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computing, networked systems, and beyond. The work will range from theoretical and algorithmic development of distributed protocols and coordination mechanisms, through the design and implementation
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algorithms, and experimental systems research, and is closely connected to advanced-level teaching in computer systems and cybersecurity. About the research project This doctoral student position is part of a
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critical functions in inter-cellular communication, controlling tissue development, homeostasis and repair, inflammatory and immune responses, neuronal connectivity, and symbiosis with bacteria. However
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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). Completed courses in signal processing, radar or communication systems. Communication skills in Swedish are valuable, but not required. What you will do Develop radar signal processing and algorithms
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myocardial infarction or stroke. To better understand the development and progression of vascular disease, over the past decades we have, together with the Vascular Surgery Clinic, Karolinska Hospital
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is on fundamental limits, and development of algorithms and methods. Applications can be found in, for example, signal, image and video processing for autonomous vehicles and swarms of drones; massive