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department at TU/e for finite element-based deformable body simulations. Conduct research on mechanical contact processing models, integrating both physics-based numerical models and data-driven approaches
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to neighborhood outcomes. In close collaboration with local stakeholders, experiments will be conducted to test model predictions and interventions. During the PhD, you will: Gain expertise in theory-driven
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Integrated photonics is maturing and integration density increases. This means the design methods and testing strategies need to keep up. Are you interested in exploring compact models and novel
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learning, as well as process-based models integrating thermal biology mechanisms. Funded by the ”Federal Ministry of Research, Technology and Space” (BMFTR), CSIDlab as part of the “Vector-borne disease
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. Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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on the integration of solar systems across spatial scales, linking resource characterisation, building physics, and data-driven modelling. The research is conducted in close connection with the INES platform (Institut
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-driven probabilistic risk assessment models and inspection planning balances cost of inspection and risk of failures, and accounts for reliability and safety. Furthermore, inspection decisions and safety
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events, will be used to enhance the diagnostic and predictive capabilities of the safety level for the individual lift. Combining data-driven probabilistic risk assessment models and inspection planning
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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PhD studentship: AI-Driven Fall Detection from Floor Vibrations Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project