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Field
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Criteria Ideal applicants will have postgraduate qualifications in epidemiology, biostatistics, public health, or another similar field. They must also meet the English language proficiency requirements as
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. Postdoctoral Research Fellow in Biostatistics and Bioinformatics Duke University is seeking a postdoctoral research fellow in the Department of Biostatistics & Bioinformatics (https://biostat.duke.edu/) within
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opportunities for grant writing and collaborative writing projects are also possible. Qualifications Ph.D. in psychological sciences, human development, speech and/or language, neuroscience, biostatistics or a
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institutions in the fields of biostatistics, epidemiology, meta-research, population health science, public health, and medical informatics. The scientific coursework serves to deepen methodological knowledge
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, metabolomics, biostatistics, etc.) and soft skills courses (scientific writing, scientific presentation, intellectual property rights, project management, good scientific practice, career coaching, etc.) can be
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, biostatistics, bioinformatics, and theoretical physics. Recently, AI (AlphaFold, computer vision, etc.) has had a huge impact on life science, proving that this field is constantly changing. The mission of QMB is
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. Advanced training modules: Choose from practical courses and lecture series on topics like image analysis, microscopy, biostatistics, developmental biology, and more. Community & collaboration: Take part in
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epidemiology, biostatistics, public health, or another similar field. The applicant will need to meet the minimum eligibility criteria for admission. Application Procedure Interested applicants should send
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project management on a large clinical trial. Required Qualifications: A Ph.D. in health services research, health outcomes, epidemiology, health economics, health informatics, biostatistics, or a closely
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Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or related discipline. * At least 1 year of experience in bioinformatics research. * Quantitative training with good understanding