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create objective, reliable, and scalable methods for measuring behaviors that support communication, learning, social engagement, and developmental outcomes for children and families. What You'll Do
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multiple affiliations. POSTDOCTORAL ASSOCIATE OPPORTUNITY Acharya Lab – Division of Structural Biology The Acharya Lab in the Division of Structural Biology at the Duke Human Vaccine Institute (DHVI) is
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. Must have a desire to design, execute, analyze, archive, review wet lab experiments in a manner that is scientifically justifiable, reliable and understandable to others under the guidance of your
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modeling and analysis. Ability to select, implement, diagnose, and adapt parameter-estimation or statistical-inference methods to suit the model, data structure, and scientific question. Experience with
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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. Postdoctoral Associate in Structural Biology & Biophysics Lee Lab | Duke University School of Medicine A NIH-funded postdoctoral research position is available in the laboratory of Dr. Seok-Yong Lee at the Duke
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research team. The postdoctoral researcher will conduct independent and collaborative research on the biochemical, structural, and mechanistic characterization of enzymes involved in natural product
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on the development of a calibrated agent-based HIV epidemic simulation representing populations in the U.S. South. The model will incorporate realistic network structures, behavioral dynamics, treatment uptake and
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, or physician-scientist support roles. Position Structure This is a full-time position; the contract is annual with the option to renew. Because MICRO-ICU is an active prospective clinical study, the position
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electron microscopy experiments, including STEM, TEM, and related characterization techniques, to investigate the structure–property relationships of energy and quantum materials. 2) Perform advanced data