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. The candidate will apply a suite of statistical and physical models for integrating observations of different accuracies, improving predictions of future hazards. The work will further include research, writing
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, healthcare utilization, quality of care, and patient outcomes across the cancer continuum. Conduct advanced statistical and epidemiologic analyses using large-scale administrative health databases, including
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pipelines and documentation Contribute to study design, interpretation of results, and preparation of manuscripts and presentations Required Qualifications PhD in bioinformatics, computational biology
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qualitative and/or quantitative data from a variety of sources, and contribute original ideas for new research projects. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics
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of multi-modal healthcare record data. The ideal candidate will additionally have experience: Multi-modal AI model development Statistical modelling techniques (Bayesian inference, differential equations and
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concerns applied science for and often with public and private partners. Job requirements We are looking for a highly motivated researcher with: A PhD in a relevant discipline, such as urbanism
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experience in: Mammalian cell culture. High-performance computing environments. UNIX and Python and/or R. Reverse genetics systems or viral culture. Advanced statistical or computational data analysis
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● A PhD (or foreign equivalent) in Computational Biophysics, Biochemistry, Chemistry, Bioinformatics, or a
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of Dentistry, Oral & Craniofacial Sciences at King's College London. Our methodological work spans trustworthy AI, multimodal machine learning and statistical signal processing. Our translational work applies
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Medicaid and/or Medicare data, a deep understanding of analytical methods and statistics, and advanced programming skills are therefore desired. The role will also involve serving as an author on selected