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, Physics, Electrical Engineering, Mechanical Engineering, or related field Knowledgeable in machine learning, deep learning, python, PyTorch, and programming in general. Knowledgeable in transformers and
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prevalent in our daily lives, we need guarantees of correctness in sensitive areas. The CertAI project aims to advance in this direction by leveraging certified model counting to certify machine learning
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phase-field simulations. Experience in developing AI or machine learning models for physics-based scientific or engineering applications. Proficiency in Python, scientific computing and machine learning
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models to quantify infection dynamics and therapeutic response endpoints • Develop and apply machine learning and AI-based approaches for pattern recognition, predictive modeling, and target discovery
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mechanics, information theory, stochastic processes, population dynamics, and neural networks. Within this framework, machine learning systems and artificial generative models will also be considered, where
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industrial partners. Main activities: • Develop constitutive models for granular media using physics-informed Machine Learning — high responsibility • Implement a coupled learning / boundary value problem
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. Candidates should have: • A demonstrated record of original research in NLP, machine learning, or a related area • Experience conducting empirical research with large language models • Strong programming and
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and Ni and with energy densities exceeding LMFP and competitive with NMC. A postdoctoral research position is now available on this 3D-CAT project in the area of computer modelling and materials design
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 12 days ago
and physical oceanography, data assimilation and machine learning. Gathering this large panel of skills, the team aims at improving our understanding, reconstruction and forecasting of ocean dynamics
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. The position combines Empa UESL’s expertise in developing and accessing energy system models with the methodological expertise of the IMOS Laboratory in machine learning and foundation models. Postdoctoral