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microbiomes, and predictive models linking molecular and clinical data to cancer risk stratification. The work will be carried out in close collaboration with computational researchers at DTU and
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Engineering«. The work involves simulating cavitation at three model levels, ranging from single-phase descriptions and population balances to detailed two-phase simulations of individual bubbles. All models
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, hydrological and land-cover data, and applying approaches such as the InVEST Urban Cooling Model and relevant flood-analysis methods. Coordinate field measurements and model validation along selected
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Toxicology Division we aim to improve the scientific basis of chemical risk assessment through fundamental and applied innovative research, teaching and training in mechanistic and predictive toxicology
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record in marine evolutionary genomics who investigates rapid evolutionary responses—such as evolutionary rescue—through field studies and/or experimental evolution in the laboratory. Preferred model
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. Working together with researchers at DTU, UQ, and Danfoss, you will combine thermofluid modelling, reduced-order multiphysics methods, and nonlinear rotor dynamics analysis to develop predictive
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model predictive control, machine learning, or reinforcement learning. Experience with IoT, edge computing, and cloud integration. Proven ability to contribute to research funding proposals
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written and spoken English. Experience with some of the areas of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi
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for disease progression modelling, acute event prediction, hospitalization risk estimation, and health vulnerability assessment; Contribute to model interpretability, uncertainty estimation, fairness
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conservative heuristics, even where substantial data exist. The project Predictive, Resilient, Integrated Systems for Management of Tunnel (PRISM-T), funded by the SNSF, addresses this challenge