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such as Bayesian modelling and optimal control theory. Using state-of-the-art methods – including virtual reality, wearable sensing, motion platforms and advanced data analytics – you will place particular
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biostatistics faculty collaborating with the Childhood Cancer Survivorship Program (CCSP). You will develop innovative biostatistical methods for childhood cancer survivorship research and collaborate with CCSP
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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for students, line-manage Research Assistants and D.Phil. students, mentor on methods, analysis and career development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g
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, SEC, UV-Vis, and related methods. Conducts in vitro evaluation of lead compounds, including stability, binding, pharmacologic, and functional assays. Participates in radiolabeling studies and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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, ocean data assimilation, and computational methods for understanding and predicting regional and coastal ocean circulation. This is a full-time position for 2 years, with the possibility of a 3rd year
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. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from the SPRUCE (Spruce and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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molecular representations, off-target prediction, and experimental feedback. The developed methods will be applied in iterative prospective drug-discovery cycles, with a serine protease from the complement