2,394 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs in United States
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will have an opportunity to learn or become more proficient in the techniques used in the lab, including lung organoids, precision cut lung slices, transgenic rodent models, preclinical models of lung
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excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases
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. This is a full-time, in-person position based in South Bend, Indiana. The twelve-month annual salary is commensurate with NIH postdoctoral salary guidelines (https://www.niaid.nih.gov/grants-contracts
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this diversity. Our research spans comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced
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. This position will focus on developing and applying novel statistical methods, machine learning approaches, and AI-driven computational tools, with a strong focus on statistical genetics and genomics
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or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer work to generate
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learn how to lead community pharmacy-based patient care practice initiatives and to advocate and collaborate with various stakeholders to bring about change in pharmacy practice. Through real world
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Postdoctoral Associate: Neurodegeneration – Hu Lab, Weill Institute (Research & Innovation) Postdoc Associate: Neurodegeneration – Hu Lab, Weill Institute Weill Institute The Fenghua Hu lab (https
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL