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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
environment. Desirable qualifications Strong knowledge of statistics, statistical learning, or probabilistic modeling. Experience collaborating with experimental scientists, biologists, or clinicians. Interest
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environments, and distributional shifts. The research will combine probabilistic modelling, network-based representations, and modern AI methods to enable scalable and interpretable decision-making in complex
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and behavioural experimentation. Key research tasks include: Developing learning-based behavioural models of navigation, route choice and adaptation; Applying reinforcement learning, probabilistic
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environment. Particularly advantageous Strong knowledge of statistics, statistical learning, or probabilistic modeling. Experience collaborating with experimental scientists, biologists, or clinicians. Interest
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probabilistic tracking mechanisms (e.g., shared identifiers, IP correlation, fingerprinting (see [1]), or behavioral synchronization). Investigating how tracking companies and SDKs operate across device and
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notions of resilience have to be developed along with algorithms to check resilience of machine learning models. Research is conducted in the fields of automated reasoning, probabilistic verification, and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
methodologies to complex engineering systems; Development and application of advanced Scientific AI methodologies, including surrogate models, generative models, probabilistic models, and data-driven and physics
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
illustrates a growing mastery of the theoretical and applied challenges of modern probabilistic inference. Inria Grenoble's Datamove team has a long-standing collaboration with EDF. We co-developed the Melissa
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of surface water, groundwater, and probabilistic seepage analysis, together with modelling and uncertainty assessment techniques. Consideration of these interacting processes may help improve the accuracy and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
-informed/physics-guided models to complex engineering systems Development and use of advanced scientific AI methodologies, including surrogate models, generative models, probabilistic models, and both data