Post Doctoral Fellow-MSH-76880-013
About the role
The Suarez-Farinas Lab at the Icahn School of Medicine at Mount Sinai seeks a highly motivated postdoctoral fellow to work at the intersection of artificial intelligence, causal inference, and translational health data science. Research focuses on developing rigorous statistical and machine learning methods to uncover disease mechanisms, identify treatment-response biomarkers, and advance precision medicine using clinical trials, real-world data, and multi-omics datasets. The postdoctoral researcher will lead and contribute to cutting-edge projects involving AI and data science in healthcare.
Responsibilities
- Designing studies
- Developing novel algorithms
- Analyzing large and complex datasets
- Collaborating closely with clinicians and interdisciplinary teams
- Contributing to high-impact publications
- Presenting at leading conferences
- Mentoring junior trainees
Qualifications
- PhD in statistics, biostatistics, computer science, data science, bioinformatics, or a related quantitative field
- Strong background in ML and interest or experience in causal inference (e.g., causal ML, treatment effect estimation)
- Proficiency in R and/or Python, with experience handling large, complex datasets
- Solid understanding of statistical modeling, experimental design, and algorithm development
- Experience in biomedical or healthcare research is a plus
- Demonstrated ability to work independently and collaboratively in a multidisciplinary environment
- Strong written and oral communication skills
- Experience mentoring or teaching is desirable
Application
This is a full-time postdoctoral position. Applications will be reviewed on a rolling basis. To apply, please email a CV and the names of three references to Mayte Suarez-Farinas (mayte.suarezfarinas@mssm.edu) with the subject line ?Postdoc Position.? SPOC-UAW Local 4100 at Icahn School of Medicine (Post Docs), 811 - Population Health Science and Policy - ISM, Icahn School of Medicine