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manuscripts, conference presentations, and other dissemination of project findings. 10% – Project Management Work directly with the PIs to ensure efficient progress toward project objectives. Coordinate
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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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research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research/groups/remotesensing ). We are a growing, lively
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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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for Physical Geography and Hydrology, which has long-term experience in investigating the terrestrial cryosphere and is involved in various high-level research projects and centers. (See for instance http
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
for multiple-object tracking," IEEE TPAMI, 2022. 4. L. Vaquero, Y. Xu, X. Alameda-Pineda, V. M. Brea, and M. Mucientes, "Lost and found: Overcoming detector failures in online multi-object tracking," ECCV, 2024
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stimulating the positive and sustainable behaviours needed to address ongoing environmental challenges. The research will be developed within the broader scientific objectives of NATURETIME. The specific focus
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neural networks, covering representation, optimisation, generalisation, robustness and reliability, while remaining sufficiently tractable to inform engineering practice. A key objective is to transform
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for Industry and Risk Management" CAP (Collaborative Acceleration Program) initiative, from the PostGenAI@Paris hub coordinated by Sorbonne Université. Objectives: The project addresses a central challenge in
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entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools