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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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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 | 8 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
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in physics-informed machine learning, surrogate modelling, generative AI, or design optimisation would be desirable. An entrepreneurial mindset and a willingness to build commercial acumen alongside
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to learn new methods and domains and to transfer approaches across them. The role centers on developing modular, acquisition-aware AI foundation models and applying them to large-scale scientific and
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. This postdoctoral fellowship in the Arlotta lab involves computational analysis of large, multimodal single-cell datasets, as part of a collaborative project which also aims to generate AI and machine learning models
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 8 days ago
and Objective: Tabular and Time-series foundational models have become very popular due to their high accuracy relying solely on In-Context Learning (ICL) [3, 4]. However, one still requires training