Postdoctoral Associate - cancer epidemiology

Monday - Friday, 8 a.m. - 5 p.m.

Summary

The Section of Epidemiology and Population Sciences at Baylor College of Medicine invites applications for a Postdoctoral Associate position for our Cancer Epidemiology with Real-World Data (RWD) Training Program. The Training Program provides epidemiology and bioinformatics Postdoctoral Associates with training in how to combine traditional epidemiologic research methods with RWD and modern technologies, like artificial intelligence and natural language processing, for impactful cancer research. Exciting opportunities also exist to work with faculty from MD Anderson Cancer Center, Rice University and UTHealth School of Biomedical Informatics.

Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

Job Duties

• Analyzes large data sets.
• Analyzes next generation sequencing data (e.g., RNA-seq, whole genome/ exome sequencing) to address complex biological and translational research questions.
• Uses state-of-the-art bioinformatical and statistical tools.
• Develops new statistical methods to answer biological questions that arise in the research.
• Prepares manuscripts, abstracts, and presentations for peer-reviewed journals and scientific conferences.
• Ensures compliance with institutional, sponsor and data security guidelines for handling sensitive genomic and clinical data.
• Conducts advanced analysis of large-scale biomedical and population health datasets to support ongoing research within the section.
• Collaborates with multidisciplinary teams that includes faculty investigators, statisticians, clinicians, and trainees, in a highly team-oriented research environment.
• Participates in the Section's sponsored training program by contributing to collaborative projects, mentoring trainees, and engaging in programmatic activities such as seminars, workshops, and collaborative research initiatives.
• Develops methodologies and tools for use in the electronic medical records that will strengthen the Learn Health System and improve patient outcomes.
• Performs other job-related duties as assigned.

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Ph.D. in Epidemiology or Bioinformatics or related field.
• Prior experience in analysis with real-world data, high-dimensional data, causal inference, and/or machine learning /artificial intelligence in a plus.
• Knowledge in cancer biology or genetics is desired.
• Excellent writing skills in English.
• Ability to work in a team environment.