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their connection to the group’s activities in their cover letter. Possible research topics include: Collaborative, federated or decentralized learning/Continual learning and knowledge sharing/Optimization
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learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
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chemistry modelling techniques scientific machine learning high-performance computing molecular design, generative AI, database handling and analysis collaborative, project management, presentation and
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library. Strong interest in machine learning, reinforcement learning, and fluid dynamics. Ability to work independently and collaboratively in an interdisciplinary team. Excellent command of English, both
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Job Description The section for Atomic Scale Materials Modelling (ASM) at DTU Energy is looking for two outstanding candidates for PhD scholarships within the field of Geometric deep learning
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combining engineering and life sciences, through challenge-based learning and a multidisciplinary approach in collaboration with hospitals, industry and others, the department addresses the great challenges
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learning, and porous materials strong analytical and problem-solving skills ability to work independently and collaboratively in an interdisciplinary team excellent communication skills in English
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, or low-power hardware. Key research directions include (but are not limited to): Data-efficient learning: Zero-shot and few-shot recognition, semi-supervised learning, and techniques that reduce reliance
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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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explore multimodal learning and unlearning techniques using vision, language, and audio signals to build intelligent systems capable of interpreting and responding to human actions and emotions. This work