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researchers develop new machine learning (ML) methods to tackle challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division , our group
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that include machine learning components, and on cooperation with industrial partners and with the TECoSA competence center at KTH. The Division of Network and Systems Engineering conducts fundamental research
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reconstruction. We will use physics modeling, machine learning and experiments to develop new and improved methods for using data from energy-sensitive x-ray detectors to improve the diagnostic quality of x-ray
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-Physical Systems, you will teach at undergraduate and postgraduate level, including courses in computer architecture, embedded software, real-time systems, and AI-based perception for cyber-physical
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computing Teach, including supervising master’s students and working as a teaching assistant Take courses at PhD level Contract terms The Doctoral student positions are fully funded from start. The position
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Technology We invite applications for a fully funded WASP-PhD position to join the new research group of Martin Trapp to work on the reliability and trustworthiness of machine learning models. You will work
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a Research Infrastructure? No Offer Description This PhD project covers a broad range of research topics in network security, with priority given to candidates interested in the network-layer security
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data types (transcriptomics, proteomics, imaging). AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. FAIR
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5 Dec 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Computer architecture Computer science » Programming Computer science » Other
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This PhD project covers a broad range of research topics in network security, with priority given to candidates interested in the network-layer security challenges of distributed systems like