Postdoctoral Fellow (Cancer Epidemiology)
University of Maryland School of Medicine
Department of Epidemiology and Public Health, Division of Cancer Epidemiology
Postdoctoral Fellow/Research Associate/Data Scientist in Genomics Research
Description: A research fellowship is available at the University of Maryland School of Medicine in the Department of Epidemiology and Public Health. The fellowship will provide opportunities and experience in genomics research to prepare individuals for positions in academia, government, or private industry.
Prospective candidates are expected to contribute to study design, implementation, project management, data analysis, and manuscript development . The candidate will work with multidisciplinary teams across several departments and institutes at the University of Maryland School of Medicine, other U.S. and international universities. The context of the research is to implement genomics methods and analysis, collaboratively generate and refine risk scores by integrating existing datasets with genomic and phenotype data for a range of complex diseases and traits. Training includes mentored research, grant-writing, and teaching experiences.
Research fellows receive a competitive salary and benefits.
Interested applicants should apply online through the University of Maryland, School of Medicine website (https://www.umaryland.edu/jobs/), job ID #210000E1 and include: a cover letter, CV, research statement, and contact information for three references.
The University of Maryland, Baltimore is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy.
Qualifications: This position requires strong skills in genomics analysis and knowledge of data science. Those with a PhD, ScD, or DrPH in epidemiology, genetic epidemiology, biostatistics, data science or related fields are strongly encouraged to apply. Excellent communication, organizational, inter-personal, and time-management skills are a must.
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