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of Clinical and Preventive Nutrition Sciences at Rutgers School of Health Professions is seeking a highly motivated Postdoctoral Associate to join an active research program focused on maternal and
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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of the Director of PopQuIS, Program faculty, and designated mentors, the Post Doctoral Associate conducts specialized research, literature review and integrates a primary care framework to improve population and
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of the Director of PopQuIS, Program faculty, and designated mentors, the Post Doctoral Associate conducts specialized research, literature review and integrates a primary care framework to improve population and
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Number: 269896 Minimum Education and Experience: The individual must have completed a PhD in biology, biochemistry, molecular biology, or metabolic engineering with extensive computational research and lab
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for Regulatory Science, the Center of Excellence for Rapid Surveillance of Tobacco, the Tobacco Dependence Program, a Tobacco Industry Marketing Program, and a Tobacco Control Law & Policy Resource
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The individual must have effective skills in teamwork and problem-solving and be adaptable to changes in technological and scientific directions. Effective oral and written communication skills. Must be computer
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-Medina’s Neuroinformatics for Personalized Medicine lab in McGill University, Canada. Applicants must have experience working with computational modeling and multi-omics analysis in neurodegeneration. Ideal
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in a program at an accredited college or university, studying computer science and/or a related discipline. Certifications/Licenses Required Knowledge, Skills, and Abilities Python LLM RAG Fine-tuning
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including a Tobacco Center for Regulatory Science, the Center of Excellence for Rapid Surveillance of Tobacco, the Tobacco Dependence Program, a Tobacco Industry Marketing Program, and a Tobacco Control Law