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Field
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
-driven and physics-informed learning techniques Development of simulation-based optimization methodologies, including Bayesian optimization, derivative-free optimization, multi-objective optimization
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imaging and in vitro/in vivo tracking. A central objective of the project is to understand the fundamental mechanisms governing nanoparticle formation and drug compartmentalisation during PISA. To achieve
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
-informed learning techniques; Development of simulation-based optimisation methodologies, including Bayesian optimisation, derivative-free optimisation, multi-objective optimisation, model calibration, and
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
covers the object's entire life cycle and uses real-time data sent by sensors on the object to simulate its behavior, monitor operations, and anticipate its functioning. Partial differential equation (PDE
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objective is to develop methods that move beyond correlation-based prediction toward causal reasoning, intervention-aware modelling, and interpretable AI systems. This transition from correlation to causation
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power take-off under realistic environmental and operational conditions. A key objective of the project is the development of probabilistic and physics-informed models to quantify uncertainties related
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systems, and multi-objective optimization. Prof. Freja Nygaard Rasmussen – life cycle assessment Prof. Sebastien Gros – decision-making, energy use, AI and machine learning Dr. Signe Riemer-Sørensen - AI
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systems, and multi-objective optimization. Prof. Freja Nygaard Rasmussen – life cycle assessment Prof. Sebastien Gros – decision-making, energy use, AI and machine learning Dr. Signe Riemer-Sørensen - AI