Postdoctoral Research Scientist

The Department of Radiology at Columbia University has research teams applying advanced imaging AI and clinical data science, as well as quantitative disease modeling to address pressing challenges in health outcomes and policy. Dr. Kang's research laboratory is focused in personalized testing pathways, translation of diagnostic innovations, and cancer screening. We develop predictive models, simulation frameworks, and AI-driven analytic tools to inform screening, prevention, and treatment strategies. Dr. Kang is a physician scientist and leader in cancer simulation modeling working with multiple collaborative teams across the university.

Duties and responsibilities:

Position Benefits

• Direct involvement in high-impact healthcare and precision medicine studies, particularly in cancer early detection, screening, and treatment modeling.
• Publication opportunities.
• Mentorship and career development support from Columbia faculty.
• Opportunity to build a path toward long-term academic faculty roles.

Position Description

We are seeking a highly quantitative, research-oriented postdoctoral scientist with strong AI/data science and statistical modeling expertise. The ideal candidate will have advanced coding skills and a deep interest in translating quantitative methods to impactful problems in healthcare and population health. The position offers:

• Independent research opportunities in AI-driven prediction modeling, statistical methods, and clinical/public health applications.
• Collaborative leadership, including mentoring junior analysts and working closely with a diverse team of clinicians, data scientists, and engineers.
• Clear academic trajectory, with potential for transition to a faculty position through NIH/NSF career development grants.

• Doctoral degree (PhD) in a quantitative field: computer science, data science, bioinformatics, statistics, applied math, biomedical engineering, physics, or related discipline.
• Proficiency in programming and data science tools (Python, R, C++, or equivalent).
• Strong statistical and machine learning background, with ability to develop and evaluate prediction models.
• Excellent critical thinking, communication, and team leadership skills.

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.