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Danfoss, you will combine thermofluid modelling, reduced-order multiphysics methods, and nonlinear rotor dynamics analysis to develop predictive modelling tools that support the industrial design of
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geochemical alteration occurs, and the associated uncertainty in predicting reservoir behaviour. This will be done with laboratory investigations and geochemical modelling. Specifically, you will: Characterise
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, which charts how cognitive disorders, pharmacological interventions, and brain stimulation reposition the brain within a shared functional space, revealing principles for prediction and control. We
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modality-specific encoders, cross-modal fusion, acquisition-aware conditioning, and prediction heads. Develops and applies self-supervised training objectives (e.g., masked signal modeling, cross-modal
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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disturbances. Current control methods generally rely on simplified interaction models based on constant aerodynamic coefficients, quasi-static approximations, potential flow models, or experimentally identified
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Develop advanced models to understand and predict piping
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processing, AI-assisted code development, workflow benchmarking, molecular pattern recognition, and integration of experimental analytical chemistry with predictive modelling. We seek ambitious candidates with
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and numerical models that predict material deformation, force transmission to cells and the resulting changes in cellular mechanics and signalling. The position is primarily computational, but a
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curated pharmaceutical science and public health databases that can be used for modeling purposes. Information about Dr. Zhu’s research and recent publications can be found on his lab website: https