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Details Title Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI School Harvard T.H. Chan School of Public Health Department/Area Biostatistics Position Description
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expertise in discrete choice modelling, statistical modeling, traffic simulation, machine learning, and optimization techniques. • Strong expertise in discrete choice modelling, statistical modelling, and
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responsible for the design, documentation, analysis and reporting of linked and surveillance health data research conducted by The Kirby Institute. The position holder’s primary obligation is the statistical
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Memorial Sloan Kettering Cancer Center | New York City, New York | United States | about 20 hours ago
, bioinformatics, computer science, biomedical informatics, statistical genetics, biostatistics, statistics, engineering, or a related field. Expertise in at least one of the following areas: textual analysis
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methodologies (longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses
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postdoctoral position supported by the Simons Collaboration on Universal Statistics in Number Theory. The Postdoctoral Fellow will conduct research in one or more of the areas supported by the Simons
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methodologies (longitudinal designs, moderation and mediation, causal inference), library research (Pubmed searches, systemic review methods), and statistical analysis (data visualization, descriptive analyses
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• PhD degree in Science or Engineering • Education or a track record in applied mathematics, with a strong interest in physical sciences • A solid foundation in thermodynamics & statistical
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project funding. Purpose of the post The Senior Research Fellow will lead the development and application of advanced mathematical and statistical modelling methods to support clinical and infectious
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areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and