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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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your skills or acquire new ones, excellent medical insurance, subsidies for the use of public transport (85%) and the staff canteen, holidays and a variety of cultural and sports activities. Home working
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
environments. To achieve this, novel alignment and editing techniques are required. Specifically, post-training with Reinforcement Learning (RL) presents a highly promising methodology to overcome
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
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generation of MOF water adsorbents with optimal indoor air humidity control performance by leveraging state-of- the-art high-throughput (HT) computational screening based on Machine-Learning Interatomic
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subject The DEEPICE project aims to develop an automated workflow combining glacial geomorphology, remote sensing, DEM analysis and deep learning to detect and analyse subglacial bedforms at large scale
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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong