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this simulator to support the assessment of the FORUM mission performances. Investigating the capabilities of artificial intelligence foundation models for Earth Observation and preparing their integration
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to correct or account for these biases, and build predictive models that simulate biological responses to in silico perturbations such as genetic or pharmacological interventions. The project aims to advance
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arrays) from experimental data, leveraging training on simulated datasets. Interpretable neural networks for physics: Development of interpretable deep learning models for identification of matter phases
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combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
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al. 2019] and point-force Lagrangian models, with advanced post-processings [Vegad2024]. This work will be carried out with the YALES2 high-performance platform. Where to apply Website https
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evaluation of modal-decomposition techniques applied to data from high-fidelity numerical simulations of landing-gear aeroacoustics. The researcher will develop and implement modal-decomposition methods using
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 13 days ago
or almost completed) in Physics, Applied Mathematics, Complex System or a related field. Strong background in mathematical modeling, machine learning, or biophysical simulations. Demonstrated interest in
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probes and in combination. More specifically, the project requires developing the SBI framework including simulations as forward models of observables, performing inference on synthetic datasets and
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a Research Infrastructure? No Offer Description Work Plan • Survey of the state of the art in predictive and analytical models applied to sports, ranging from statistical and linear approaches to deep
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Posted by Kate Stuart on Wednesday, March 18, 2026 in Job Opportunities . Recent studies from the lab (https://cruchagalab.wustl.edu/ ) have demonstrated that circular RNAs