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at the intersection of artificial intelligence and cultural heritage. The successful candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital
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neural networks inspired by the human brain and examine what mechanisms enable the networks to acquire human-like intelligence. For more information, please visit our lab homepage. We are currently seeking
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Infrastructure? No Offer Description Electroencephalography (EEG) and magnetic resonance imaging (MRI) can detect early alterations in neural networks that manifest as cognitive and sleep-wake cycle disorders in
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the DDLS Fellows program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures
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Physics and AI: Physics-Informed Machine Learning (PIML): Physics-informed neural networks, with applications to Fluid dynamics, plasma physics, elasticity, weather modeling AI for Scientific Discovery in
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rendering, Gaussian splatting, etc.). Knowledge of graph neural networks. Experience in deploying and fine-tuning DL models, also large language or vision-language models. Practical experience on deploying ML
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-atlantique.fr) and Associate Prof. Christophe LOHR Keywords: Conversational Agent, Debate, Argumentation, Knowledge graph, Generative Neural Networks, Mental health preservation Where to apply Website https
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Learning, particularly Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models, including hands-on implementation Strong understanding of machine learning models
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analysis) to compare brain responses with predictions of computational models (deep neural networks developed by the NASCE team). The objectives include assessing how the brain segments, groups
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-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human