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Field
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter
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. Implement, adapt, and evaluate ML and NLP algorithms for scientific and security applications. Work in interdisciplinary collaborations with subject matter experts from a variety of domain sciences and
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in one or more of the following areas: algorithms, analytical derivation, data analysis, coding, or mathematical modeling. Strong programming skills are highly desired. The candidate should demonstrate
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quality algorithms and products (e.g., temperature, turbidity, chlorophyll-a) while developing novel methodologies to advance research on short- and long-term water quality conditions. Approaches may
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learning field. Excellent programming and computer science skills. Preferred Knowledge, Skills, And Abilities Practical experience developing novel ML, LLM, or CV algorithms and models. Experience with state
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imbalanced cross-sectional imaging data are especially well-suited for the position . The postdoctoral researchers will develop algorithms for deployment at our prestigious R Adams Cowley Shock Trauma Center
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collection, and data analysis. Work activities may include the following. • Developing analysis tools to extract physical meaning from in-situ process data. • Developing machine learning algorithms to drive
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on the design, development, and realization of future communications technologies. You will be part of the team and contribute to ongoing developments in theory, algorithms and translation to practice in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across the US with whom UNC is partnering to implement data collection and analysis