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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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organisational, communication, and relationship management skills. • Strong computer literacy, including Microsoft Office applications and database management systems such as REDCap. • The ability to work
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transportation contexts, and machine learning classifiers Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions
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, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno-economic study, design and analysis of integrated systems. Experience with energy system
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to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
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the following will be a plus: • Optical instrumentation, single-molecule/ super-resolution microscopy, magnetic/optical tweezers, ultrafast spectroscopy, or other in-situ operando imaging tools • Machine
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denoising, cell segmentation and the analysis of cellular neighbourhoods and cell–cell interactions. Experience in developing artificial intelligence and machine-learning methodologies for multimodal data
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: The R2L Lab explores how language understanding improves machine learning efficiency and generalization. We are a leader in agentic benchmarks and evaluation; our platforms serve as primary evaluation
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technology or Artificial Intelligence (AI) tools to solve business or administrative problems, demonstrated knowledge with Machine Learning (ML) and AI tools. Strong integration experience in enterprise
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relevant background in information extraction, entity resolution/entity linking, machine learning, uncertainty modelling, explainable AI, or a closely related area, with a PhD (or near completion) in