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Field
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Statistical methods are leveraged in many scientific applications to: specify a data collection practice (experimental design), draw conclusions from sparse and noisy data (inference), and assess uncertainty about those conclusions (uncertainty quantification). Bayesian inference and...
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of Applied Engineering is looking for a full-time (100%) doctoral scholarship holder in the field of robust artificial intelligence for industrial process optimisation. The research of this PhD position will
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Job related to staff position within a Research Infrastructure? No Offer Description This PhD project investigates methods to improve the robustness and compliance of multi-modal AI systems
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strategies that are robust with respect to perturbations and capable of balancing multiple competing performance criteria. Information Uncertainties are inherent in many engineering design problems and can be
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Technology, and the PhD student will be positioned in the Esbjerg Energy section. The position is part of the internally funded research project SURGE: Speed-optimized USVs for Robust Guidance and Offshore
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primary regenerative braking. EMBs are highly sensitive to EV harsh operating conditions. This project addresses this challenge by developing AI-based EMB clamping force estimators and robust control
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
, expertise, and powerful computational resources (GPUs & CPUs) of the team. This PhD position is fully funded within the framework of RoGSiLT: Robust and Generalizable Sign Language Translation , a
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This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible to apply (more details can be found here ). The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be...
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Fully Funded PhD Studentship (Home Fees) Project Title: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data Supervisor: Professor Angela Wood (Professor of Biostatistics and
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provided by Dr Noémie Hamilton at the York Biomedical Research Institute and the Department of Biology at the University of York. You will focus on developing and standardising robust preclinical outcome