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language models (gLLMs) with their applications to genetics, e.g. in identifying causal genes for Alzheimerâ™s disease (AD). You will have access to state-of-the-art computational infrastructure such as A100
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environments, cloud computing, or GPU-accelerated machine learning Background in Monte Carlo Tree Search (MCTS) or reinforcement learning for sequence generation Familiarity with biological sequence alignment
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computational infrastructure such as A100 and H100 GPUs, combined with pre-processed large-scale biobank data such as UK Biobank and ADSP, enabling you to work at the scale required for breakthrough research
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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); units such as onboard computers, mass memories, remote terminals and instrument control units*; digital and analogue signal processing electronics for payload/platform functions; front-end acquisition and
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grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
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Sign In Create Profile Postdoctoral Research Associate-Computer and Information Research Tucson, AZ, United States | req23101 Apply Now Share Save Job Posted on: 6/11/2025 Back to Search
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The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious new project on dexterous robot learning. In
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
the boundaries of knowledge in the many subfields spanning length scales between. Forefront physics and astronomy research requires access to well-equipped laboratories and extensive computing capabilities; it
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
the boundaries of knowledge in the many subfields spanning length scales between. Forefront physics and astronomy research requires access to well-equipped laboratories and extensive computing capabilities; it