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Field
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the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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, materials scientists, biologists, and machine learning researchers, embedded in the broader robotics ecosystem at ETH Zurich Strong ties to industry and to our spin-offs, and support for turning your research
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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technologies, including machine learning and large language models experience with containerisation tools (e.g. Docker, Singularity) and research computing workflows proven capability in data science, software
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to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and
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loading, and functional genomics. 3. Computational Modeling of pHLA Recognition and Protein Design Computational protein design, machine learning, molecular recognition, and predictive approaches
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning
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Essential MSc or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field Exceptional BSc candidates with strong engineering experience will also be considered