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our OU community can reach their potential. We recognise that different people bring different perspectives, ideas, knowledge, and culture, and that this difference brings great strength. We strive
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asynchronous AI-led chemical optimisation across chemistry laboratories”. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include: Development and application of AI and machine
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 13 days ago
to reconstruct open rose flowers in 3D. The key idea is to learn two neural networks that operate on different scales. The first network operates on the scale of the full flower to identify the flower architecture
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 7 days ago
at the Centre Inria de l'Université de Lille in the Scool team. He or she will be in contact with experts of sequential decision making. The candidate will study different research questions related
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project has a strong focus on developing and applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include
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. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model for diagnosis and prognosis of different sarcomas. He/she will develop and train
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning for batteries, with the support of
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches