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, optimization and inverse problems, computational aspects of stochastic (partial) differential equations, randomized numerical algorithms, structure-aware and structure-preserving numerical methods for continuum
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in mountainous areas. The project is focussed on collecting and analyzing a unique field data se t collected using sensors originally developed for mobile robotics applications. Job description
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directions include: Using AI to learn parameters and design circuits for quantum optimization algorithms (e.g., beyond QUBO formulations for QAOA) Developing AI-driven methods to discover quantum optimization
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also oversee the translation of materials, technologies, protocols, and AI algorithms to the clinics and industrial partners. Therefore, experience in or a strong link to clinical medicine is desired
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the perfusion hardware; developing improved control software and sensor integration for real-time monitoring of physiological parameters (pH, oxygen tension, glucose, lactate, pressure, flow); and supporting
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methods and optimisation algorithms for robust intervention planning and resource forecasting in railway infrastructure management. Characterising and propagating the principal sources of uncertainty in
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analysing time-series data from smartphone sensors and usage logs using advanced statistical and machine learning approaches to develop personalised nudging and adaptive interventions. The candidate will also
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ultrasound technologies, ultrasound-responsive drug carrier formulations, and adaptive closed-loop control algorithms as an integrated precision drug delivery platform for the brain. Our approach employs a
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without invasive surgery. Project background We develop advanced focused ultrasound technologies, adaptive closed-loop control algorithms, and ultrasound-responsive micro/nano therapeutic carriers as an