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Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | 13 days ago
well as Bayesian borrowing can help address sample size and ethical concerns for rare diseases. Collaboration between the statistician at DB9 and the clinical team at the Division of non-malignant hematology to map
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characterization (SEM, TEM, XPS, FTIR, etc.) Programming skills (Python, MATLAB, or similar) Exposure to machine learning methods (e.g., Bayesian optimization, active learning) is an advantage Understanding
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, XRF, isotopic, and tephra analysis, alongside the construction of Bayesian age–depth models using radiocarbon, 210Pb, and tephrochronology. Candidates with experience in metagenomics (sedimentary aDNA
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research objectives and proposals for own and/or collaborative research area. • Prepare papers for publication in leading journals and/or contribute to the dissemination at national/international
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, XRF, isotopic, and tephra analysis, alongside the construction of Bayesian age-depth models using radiocarbon, 210Pb, and tephrochronology. Candidates with experience in metagenomics (sedimentary aDNA
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inference (otherwise known as spectral retrieval), which involves using forward models in conjuction with Bayesian or machine learning-based techniques in order to derive posteriors on parameters of interest
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the “Inverse Problem” component of the project: developing and validating a satellite-based pancake-ice detection algorithm using ICESat-2 wave-damping observations within a Bayesian inversion framework
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Gravitational-Wave Astronomy Using Artificial Intelligence, to work on computational Bayesian inference methods and their astrophysical applications. Southampton's School of Mathematical Sciences is home to a
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or translational research experience Knowledge of machine learning, Bayesian modeling, or statistical method development Ideal Personal Attributes: Independent, proactive, and scientifically curious Detail-oriented
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Postdoctoral Fellow with Professor Samuel Kou. Professor Kou’s group focuses on research in statistical modeling and stochastic inference in protein folding, biology, chemistry and medicine, Bayesian inference