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). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with Reinforcement Learning, Deep Learning and/or Explainable AI, demonstrated for example through
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 4 hours ago
mathematical background. - Familiarity with deep learning frameworks such as PyTorch. - Commitment, team working and a critical mind. - Fluent verbal and written communication skills in English
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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Reinforcement Learning, Deep Learning and/or Explainable AI, demonstrated for example through coursework or research projects. Our offer a position for 18 months, with an extension to a total of four years upon
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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diversification and change we see across languages today. Job description This 4-year PhD project will use group communication games and artificial language learning experiments to investigate the role of social
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complex interaction patterns that may carry important biological information. By integrating deep learning, genome-wide simulations, functional genomics, and large-scale biobank data, AI:GENOMIX aims
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. Additional qualifications Experience with one or more of the following areas is meriting: Bayesian statistics, mathematical modelling, probabilistic machine learning, deep learning, large language models
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is
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open to candidates with a strong interest in either: i) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane