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collaboration with industrial and public-sector partners. We expect the candidate to publish in competitive machine learning, software engineering and security venues, such as Neurips, ICML, ICLR, ICSE, FSE, ASE
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-based methodologies for protein structure prediction and cofolding Machine learning guided virtual screening Taking on organizational tasks and writing grant applications Your Profile The ideal
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large language models (LLMs), natural language processing (NLP), and/or machine learning, with a verifiable track record (e.g., publications, thesis, or open-source contributions). Proficiency in Python
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are especially encouraged: (1) statistical mechanics, condensed-matter theory, quantum field theory; (2) tensor networks, quantum information, quantum algorithms; (3) machine learning, generative models, large
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aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as well as machine
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out
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with IBD and build novel model-informed precision dosing applications. Located in the epicenter of Silicon Valley, the Colman Lab utilizes state-of-the-art AI-assisted tools and innovative machine
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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines