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$37.12 - $59.69 (Hourly Rate). To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html
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the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The Section Fundamental
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hydrogen-ammonia co-combustion using experimental techniques, high-fidelity numerical simulations, and machine learning” The competition is open to applicants who meet the detailed requirements set out in
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technology, spaceflight robotics, dust astronomy, astronautics, electric and advanced space propulsion, the experimental and numerical simulation of atmospheric entry phenomena, the development and deployment
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between Numerical Analysis and Machine Learning, with a focus on physics-informed machine learning. The goal is to design learning strategies that embed the structure of governing physical laws, enabling
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which research focuses mainly within the research programmes (1) Algebra, Geometry and Mathematical Physics, (2) Pure, Applied and Numerical Analysis, and (3) Stochastics and (4) Discrete Mathematics and
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criteria - Master simulation tools such as SPICE, VHDL(-AMS), Cadence, as well as calculation and modeling tools such as Matlab/Octave or Python. Skills in finite-element type numerical simulation will be a
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of emissions of greenhouse gases. The reason for most of this uncertainty is that clouds are especially challenging to represent in numerical models of the atmosphere. Clouds affect the Earth’s radiation
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 1 month ago
and ML-based constitutive modeling, finite element technology, and microstructural simulation tools. This position is ideal for candidates who enjoy working in a research environment, building high
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 1 month ago
) techniques, numerous studies have explored replacing traditional constitutive models with black-box neural networks or other data-driven approaches. However, it has been shown that such black-box models may