Postdoc: AI-Driven Causal Health Data Science

Mount Sinai; United States; On-site; USD 60,000 - 70,000; Full time

Job summary

Mount Sinai in New York invites applications for a Postdoctoral Fellow in AI, causal inference, and health data science. The fellow will lead studies, develop algorithms, and analyze complex clinical data, collaborating with clinicians and interdisciplinary teams.

Candidates should have a PhD in a quantitative field, strong ML experience, and proficiency in Python or R, with excellent communication and mentoring abilities. This is a full‑time on‑site role in New York.

Qualifications

• PhD in statistics, biostatistics, CS, data science, or related field.
• Strong ML background with interest in causal inference.
• Proficiency in R and/or Python; able to handle large datasets.
• Excellent communication and collaboration skills.

Responsibilities

• Design studies and develop novel algorithms for health data science.
• Analyze large, complex datasets and validate models.
• Contribute to high‑impact publications and conference presentations.
• Mentor and train junior researchers in a multidisciplinary team.

Skills

ML

Causal inference

Statistical modeling

Communication skills

Mentoring/teaching

Education

PhD in statistics/biostatistics/computer science/data science/bioinformatics/related field

Tools

Python

R

Job description

Mount Sinai in New York invites applications for a Postdoctoral Fellow in AI, causal inference, and health data science. The fellow will lead studies, develop algorithms, and analyze complex clinical data, collaborating with clinicians and interdisciplinary teams.

Candidates should have a PhD in a quantitative field, strong ML experience, and proficiency in Python or R, with excellent communication and mentoring abilities. This is a full‑time on‑site role in New York.