Cancer Epidemiology Postdoc: Real-World Data & AI Research

Baylor College of Medicine; Houston (TX); On-site; USD 57,000 - 70,000; Full time

Job summary

The Baylor College of Medicine invites applications for a Postdoctoral Associate in Cancer Epidemiology within the Real-World Data Training Program. The position combines traditional epidemiology with RWD, AI, and NLP to advance impactful cancer research in collaboration with MD Anderson, Rice University and UTHealth.

You will work on large data analyses, develop methods, prepare manuscripts and presentations, and engage in seminars, workshops and mentoring trainees in a highly collaborative

Qualifications

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

Responsibilities

• Analyzes large data sets.
• Analyzes next generation sequencing data to address research questions.
• Uses state-of-the-art bioinformatical and statistical tools.
• Develops new statistical methods for biological questions.
• Prepares manuscripts, abstracts, and presentations for journals and conferences.
• Ensures compliance with data security guidelines for handling genomic and clinical data.
• Conducts advanced analysis of large-scale biomedical datasets to support research.
• Collaborates with multidisciplinary teams in a team-oriented environment.
• Participates in training programs by contributing to projects, mentoring trainees, and seminars.
• Develops methodologies and tools for use in electronic medical records to improve outcomes.

Skills

Team collaboration

Excellent writing in English

Education

MD or Ph.D. in Basic Science, Health Science, or a related field

Job description

The Baylor College of Medicine invites applications for a Postdoctoral Associate in Cancer Epidemiology within the Real-World Data Training Program. The position combines traditional epidemiology with RWD, AI, and NLP to advance impactful cancer research in collaboration with MD Anderson, Rice University and UTHealth.

You will work on large data analyses, develop methods, prepare manuscripts and presentations, and engage in seminars, workshops and mentoring trainees in a highly collaborative