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, quantum sensing or quantum parameter estimation. Experience with convex or semidefinite optimisation, variational methods, or computational complexity. Proficiency in relevant scientific programming
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related quantitative field. Demonstrated depth in statistical genetics methods, such as GWAS analysis, fine-mapping (for example, SuSiE), colocalization, Mendelian randomization, heritability estimation
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methods of research, testing and data collection, analysis and evaluation, and writing reports which contain descriptive, analytical and evaluative content. The purpose of this role is to acquire the
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and facilitators, develop forecasts of vaccine coverage for existing and novel vaccines (e.g. HPV, RSV, malaria), and support the design and implementation of small area estimation and reweighting
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at the sponsor's facility. Responsibilities* - Evaluate and benchmark vision-language models for adaptive robotic perception in industrial applications - Develop robust perception methods for object
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. Desirable: Research experience in quantum metrology, quantum sensing or quantum parameter estimation. Experience with convex or semidefinite optimisation, variational methods, or computational
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methods, this in close interaction with the researchers developing the in vitro cultures and models. You support the design of new experiments through model-based analysis and simulation. Discover
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Develop models, algorithms and optimization methods for resilient 6G transport networks, using machine learning where it adds value. Design mechanisms for disruption risk estimation, proactive
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to learn in international large-scale assessments in education, (b) estimation and inference methods for weighted generalized structural equation models with mixed continuous and discrete data in
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populations and routine clinical practice. This project aims to develop new methods for personalising cardiovascular digital twins at scale. The doctoral candidate will create computational approaches