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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
- UNIVERSITATEA DIN CRAIOVA
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. Nearly 90 doctoral students, a dozen post-docs, 60 master's or engineering school interns complete the workforce. Attached to the CNRS Institute of Computer Science, its research themes cover a wide
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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science. Electronic structure calculations (e.g. DFT or tight-binding methods), or thermodynamic modelling (e.g. statistical mechanics, MD or CALPHAD). Scientific data analysis. Interdisciplinary research
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-binding methods), or thermodynamic modelling (e.g. statistical mechanics, MD or CALPHAD). Scientific data analysis. Interdisciplinary research at the interface between physical sciences and AI. Personal
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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assistant professors), 7 administrative staff, and 30 members of staff who are hired on temporary contracts as research assistants, post docs or PhD students. The department puts substantial emphasis
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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to recruit up to ten PhD students and one or two Post Docs to work in parallel across the core engineering challenges of maritime nuclear propulsion, creating an unusually dense and collaborative internal
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