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learning-based surrogates for physical systems LLMs and scientific agents – large language models that autonomously reason, plan and execute scientific workflows AI for engineering design – LLM-driven agents
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to staff position within a Research Infrastructure? No Offer Description The project explores extreme light–matter interactions at the nanoscale, developing advanced theoretical models in direct
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
and broaden the scope of geophysical models. We will develop a neural solver that dynamically learns to solve the momentum conservation equations. Unlike traditional supervised learning approaches, our
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ScienceCountryRomaniaCityCluj-NapocaGeofield Contact City Cluj-Napoca Website http://www.ubbcluj.ro/ Street St. M. Kogalniceanu nr. 1 Postal Code 400084 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 4 days ago
pathways in cellular and mouse models of metabolic diseases You will perform biochemical and cell biological characterization of protein localization and organelle interactions You will apply and further
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
institutes, with the student spending substantial time at each site to leverage their complementary experimental platforms and expertise. The PhD candidate will focus on developing novel control and modeling
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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; • mathematical modelling, development of FEM models (preferably using Ansys), and simulations, particularly in the areas of electromagnetics, power losses, etc.; evaluation, verification, and optimization