Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial
- University of Oslo
- CNRS
- Constructor Knowledge Labs gGmbH
- Inria, the French national research institute for the digital sciences
- NTNU - Norwegian University of Science and Technology
- Norwegian University of Life Sciences (NMBU)
-
Field
-
behaviour, and whether a proposed composition is even admissible. The central object is not a digital twin of the application but its formal architectural skeleton: gear contracts (GearSpec), a typed
-
integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
-
of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine learning in general. OCBE
-
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
-
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
-
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
-
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
-
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
-
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