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for candidates with a background in or demonstrated ability to learn about: Bayesian methods, probabilistic machine learning or inverse modelling. Prospective applicants are encouraged to direct informal inquiries
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PhD Studentship: Designing Human-AI Teams for Meaningful Human Control of 'Machine-Speed' Operations
January 2027. This PhD explores the design of human-AI teams when the AI agents operate at ‘machine-speed’ (i.e., significantly faster than human cognitive and communication capabilities). The research will
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and quantitative security assessment
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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evidence to support the evaluation of AI and machine learning models. This may include investigating data-centric AI strategies, such as data quality assessment, annotation refinement, dataset curation, and
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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join the internationally recognised EnDROIDS programme (https://endroids.ico2s.org ) and become part of a highly interdisciplinary team of computer scientists, molecular biologists, DNA nanotechnologists
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fields of study: Computer Science, Information and Computer Engineering, Software Engineering and Management, Mathematics, or equivalent disciplines Excellent programming skills Extensive knowledge of IT
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Admission Requirements Completed Master's degree or equivalent Diploma degree Preferred fields of study: Computer Science, Information and Computer Engineering, Software Engineering and Management