102 scholarship-phd-electrical-power-engineering Postdoctoral positions at Rutgers University
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and Experience PhD, MD, or equivalent doctoral degree in Neuroscience, Biomedical Engineering, Computer Science, or a related field. Candidates in ABD (all but degree) status will also be considered
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must hold a PhD in the fields of Neuroscience, Pharmacology, Cell Biology, or a similar field, and must have a strong background in neurobehavioral approaches for pain-related behavioral testing, and
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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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administrative and analytic staff. The current PETS Center core faculty have been funded by numerous R01s, K awards, and research foundation awards. PETS Center faculty work on a variety of topics in
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projects Communicates regularly with the P.I. Maintains detailed and accurate experimental records. Supervises and trains subordinate staff. Reads current scientific and technical literature relevant
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and Experience The candidate must have a PhD degree in Microbiology, Genetics, Molecular Biology, or a related field by the position’s start date. Experience in microbial genetics and cultivation
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participate in group meetings Position Status Full Time Posting Number 26FA0692 Posting Open Date Posting Close Date 11/30/2026 Qualifications Minimum Education and Experience PhD degree in Health Informatics
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candidate(s) must hold a PhD or MD degree in Neuroscience or relevant biological sciences. Candidates in ABD (all but degree) status will also be considered. Prior experience with cell culture, biochemistry
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; Ability to publish in peer-reviewed journals, with at least one first-author publication per year. Preferred Qualifications Oral and written communication skills, including the ability to communicate
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to investigate how metabolic and molecular characteristics during pregnancy contribute to maternal and offspring health across the life course. Current projects integrate epidemiologic data with metabolomics