1,108 data-"https:"-"https:"-"https:"-"https:"-"Anglia-Ruskin-University" Postdoctoral positions in United States
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methods, molecular biology, and behavioral assays. This position offers the opportunity to lead experiments, analyze data, publish impactful findings, and present at scientific conferences—making it an
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topics, and developing optimization models and/or data-driven controls that are related to at least one of the following topics: Developing energy management strategies related to ADMS, DERMS, microgrid
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make a difference in the world! Position Information This Postdoctoral Research Associate position will play an active role in research, including working on data, presentations, publications, project
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proposals; will conduct data analysis and collaborate on reporting findings and discoveries in written and verbal form; and will manage, maintain and provide technical expertise for Benoit lab equipment
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expertise and a strong publication record utilizing advanced statistical modeling and missing data techniques, specifically multiple imputation. Strong foundational knowledge of pediatric health and clinical
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2026 The research associate will work closely with a Finance area faculty member, primarily supporting research and data analysis pertaining to the Center's various on-going research projects
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in Artificial Intelligence, Machine Learning, Quantum Information and Quantum Simulation. The successful candidate will be expected to pursue an active research program in particle theory to strengthen
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assist with grant-sponsored activities including data analysis, project development, reporting and manuscript generation. Duties/Responsibilities (80%) Carry out grant-sponsored activities including data
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design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this group span all modes of transportation including off-road, rail
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural