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Can technology learn to listen to how athletes feel, and not just to what the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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. Experience with uncertainty quantification, Bayesian inference, inverse modelling, parameter estimation, or model calibration. Experience with high-performance computing, surrogate modelling, reduced-order
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the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that integrates athletes’ subjective experiences (such as perceived exertion, motivation
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measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that integrates athletes’ subjective experiences (such as perceived exertion, motivation, enjoyment
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Creating superpositions of massive objects with a superconducting qubit: Can we test if gravity
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models for all parties in the inland shipping chain, contributing to the transition to emission-free inland shipping. The main objective of the project is the evaluation of zero-emission strategies
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the inland shipping chain, contributing to the transition to emission-free inland shipping. The main objective of the project is the evaluation of zero-emission strategies, the effectiveness of policies and
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learning objectives, and assessments used in different disciplines and how do these integrate AI guidelines? How do AI guidelines influence student learning and how should educators integrate AI guidelines