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driven individual with a PhD in data science, computer science, biomedical informatics, or a similar background with some experience working with large datasets. Prior experience with healthcare is not
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. This position is 100% on site in New Haven, Connecticut. Candidate requirements Candidates must have a PhD in Biomedical Informatics, Data Science, Computer Science, or an informatics/engineering-related field
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analysis methods, including quantitative structural analysis, network-based functional analysis, voxelwise cross-modality analyses, graph theoretic approaches, and machine-learning based applications
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of Genomic Health and Department of Genetics. Our lab uses computational and experimental methods to understand how human genetic variation underlies health and disease, across rare and common phenotypes, with
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Minimum qualifications: PhD/ScD/MD or equivalent degree and years of experience in epidemiology, econometrics (particularly around cost-effectiveness analyses), and pharmaceutical or medical device policy
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topics include, but are not limited to (i) developing statistical and machine learning methods for study designs and decision-making in early detection of pancreatic cancer (ii) establishing strategies
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, with PyTorch and/or other GPU programming tools is also necessary. You should have completed all requirements for your PhD by the time you are hired. How to Apply: Candidates who have most, but not all
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to national conferences and peer-reviewed journals. Qualifications: MD, PhD, or equivalent doctoral degree Preference will be given to candidates with the following skills: Demonstrated experience in designing
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in academia, the private sector or government. QUALIFICATIONS: · MD, PhD, ScD, DrPH, MPH or MSc (required) · Proven analytical experience in population genetics, computational biology
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are open to those with previous research backgrounds acquired during PhD or MD education. An ideal candidate would have an interest in psychiatry and/or related mental-health research. Excellent