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Eligibility criteria The candidate must have a strong background in materials physics, atomistic simulation, or numerical modeling. Experience in molecular dynamics and handling force fields is required
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Text-to-Video Generation Models Supervision : Dr Stéphane Lathuilière (INRIA-UGA) Funding : BPI contract Contexte : Recent advancements in generative AI, and in particular diffusion models [1,2], have
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lithium-ion battery models, including aging and operational constraints • Design and implement decision-support tools for industrial use cases • Analyze real or simulated fleet data • Publish research
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for environmental qualification campaigns. • Electromagnetic modelling and simulation of resonant microwave structures to support experimental investigations. • Preparation of technical documentation, including
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equation via the Cole–Hopf transformation and the associated linear problem; • quantum circuit simulation of the dynamics associated with a classical Hamiltonian via the Koopman–von Neumann (KvN
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requires very long simulation times which may only be achieved using frugal numerical approaches or reduced-order models. Below are listed some possible activities of the successful candidate. Some of these
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proficiency in spoken and written English. Experience with numerical simulation tools (CFD and/or thermal modelling) will be considered an asset but is not mandatory. Previous experience in the following areas
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collaborative research project on the topic of neuromorphic photonics using organic materials. Research activities include: - Design and modeling of integrated photonic components using electromagnetic simulation
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candidate will : • Adapt the AEROTYPro/GRASP methodology for the typing and quantification of stratospheric sulfate aerosols; • Develop optical models for the characterization of sulfate particles produced
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matter physics, with a staff of 450, including 175 researchers and lecturers. The MEM laboratory (CEA Grenoble) conducts research on the exploration of materials and devices using advanced simulation