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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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through mass media. Ability to use the computer for program delivery and management. Ability to visit clientele at sites throughout the county. Ability to plan and teach educational programs. Demonstrated
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highly collaborative research team to accelerate and extend ongoing research efforts (including DL-based joint species distribution modeling and causal machine learning) and lead methods development
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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Director, Community Engagement, Constituent Engagement, Duke Alumni Engagement and Development (AED)
retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity
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related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with transformer architectures (e.g., ViT
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Python. Other requirements to consider: Machine Learning knowledge. Specific Requirements Knowledge: Fluid Mechanics. Computational Fluid Mechanics (CFD). Aerodynamics. Wind turbines. It will be assessed
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scaling model sizes, training budgets, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on
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applications. The project integrates: Computational Fluid Dynamics (CFD) and multiphase flow modeling Radiative heat transfer Machine learning and reduced-order modeling Data-driven optimization for industrial
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Department BSD MED - Pulmonary - Patel Research Staff About the Department The Section of Pulmonary/Critical Care has been a model of exemplary patient care, research and post-doctoral training