116 Computer-Science "Data driven Materials Modeling" Postdoctoral positions at Rutgers University
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Position Details Position Information Recruitment/Posting Title PostDoctoral Associate in Artificial Intelligence/Machine Learning and Data Science Department Quantitative Biomedicine Inst Salary
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(DL), and big data analytics. His lab is developing new modeling strategies that can integrate heterogeneous public data into model development. Another major research interest is the use of large
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internationally recognized for their basic and clinical research in pharmacology, toxicology, and exposure science. Dr. Zhu’s research team has access to outstanding computational facilities for modeling, data
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internationally recognized for their basic and clinical research in pharmacology, toxicology, and exposure science. Dr. Zhu’s research team has access to outstanding computational facilities for modeling, data
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Science Foundation, and others that include a mix of research design, fieldwork, data science, simulation modeling, writing, and presentations. The overarching goal of the Postdoctoral Associate will
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. Jamie Tam, the Post Doctoral Associate will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using
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. Jamie Tam, the Post Doctoral Associate will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using
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Education and Experience PhD or MD in Neuroscience, Psychology, Cognitive Science, Public Health, or related discipline, with experience in multimodal data integration and statistical analysis
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, and agricultural impacts, among others. Successful candidates will be involved with observational data analysis, numerical modeling of natural hazards, and outreach to local stakeholders. Candidates
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longitudinal modeling, administrative data analyses, and causal inference methods. Understanding of HIPAA regulations and/or Human Subjects regulations for human subjects’ research. Excellent