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scientists Contribute to study design, analytic plans, and grant development Qualifications PhD, ScD, or equivalent doctoral degree in epidemiology, biostatistics, bioinformatics, microbiology, or a related
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, and maintain the databases and data pipelines that power COMPASS research, integrating large multi-source datasets (including ERCOT and EIA records) into reproducible analytical systems. Conduct
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the life sciences, or other comparable degree (including MD or MD/PhD) Skills and abilities Exceptional organizational and critical thinking skills, analytical practices and attention to detail are essential
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funding. Develop and apply analytical pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies to identify biological
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New York University Grossman School of Medicine (Torres-Vázquez lab) | New York City, New York | United States | 2 months ago
. The position is available immediately. Applicants should have: A PhD in developmental biology, cardiovascular biology, genetics, cell biology, or a related field. A strong publication record or clear evidence of
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studies, and how information about benefits, harms, and uncertainty is communicated to clinicians, patients, and payers. We welcome applications from recent PhD graduates and postdoctoral fellows who
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Information: The Department of Chemistry in the College of Arts + Sciences at Indiana University, consists of a well-rounded research community with cutting-edge expertise in a wide variety of modern
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benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . Minimum
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-performance computing and big data analytics PhD must have been received within the last three years. Preferred Qualifications: Demonstrated understanding of model validation, clinical trial design, and causal
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novel analytical pipelines, tools, and methods to study cancer multi-omics data Develop foundational methods and resources for the integration of single-cell and clinical transcriptomes Establish