Postdoctoral Fellow-MSH-32910-032

Mount Sinai; New York (NY); On-site; USD 60,000 - 76,000; Full time

Job summary

Icahn School of Medicine at Mount Sinai invites applications for a Postdoctoral Research Fellowship in Machine Learning, AI, and Computational Biology for Human Disease Genomics. You will work on modeling functional genetic variants and conducting large-scale PheWAS across biobanks, guided by senior supervisors in CBIPM, AIHH, and GGS.

The role offers access to extensive patient data, exome sequencing, and clinical data for advancing precision medicine, with collaboration opportunities

Qualifications

• Proficiency in programming with Python and statistical computing with R.
• Strong publication record and experience in computational biology.
• Excellent communication and presentation skills in English.

Responsibilities

• Develop ML/AI methods to model functional effects of genetic variants.
• Lead or collaborate on large-scale PheWAS studies using biobank data.
• Mentor and train junior researchers and present findings at conferences.

Skills

Python

R

English fluency

Education

PhD/MD or equivalent

Job description

Description

Postdoctoral Research Fellowship in Machine Learning, Artificial Intelligence, and Computational Biology for Human Disease Genomics

CBIPM, AIHH, GGS

Icahn School of Medicine at Mount Sinai

We are seeking applications for a Postdoctoral Research Fellowship in Human Disease Genomics, Artificial Intelligence (AI) and Machine Learning (ML), developing model to predict models to predict the functional effects of genetic variants, and to conduct large-scale Phenome-Wide Association Studies (PheWAS) in major biobanks. This fellowship will be jointly hosted by the Charles Bronfman Institute for Personalized Medicine (CBIPM), the the Windreich Department of Artificial Intelligence and Human Health (AIHH) and the Genetics and Genomic Sciences (GGS) departments at the Icahn School of Medicine at Mount Sinai in New York, NY.

We are dedicated to advancing precision medicine through cutting-edge AI techniques and human disease genomics discovery research. Key research areas of interest include, but are not limited to: developing AI/ML methods to predict disease-specific causal variants and genes, utilizing LLM and computational approaches to generate extensive databases of gain- and loss-of-function functional variants in various categories, and performing PheWAS in the Mount Sinai Million Discovery Program (MSM) biobank combined with other leading biobanks (All of Us, UK Biobank, and Million Veterans Programs) across various human populations, traits and clinical measurements utilizing electronic health records (EHR) data.

Responsibilities

Dr. Yuval Itan will supervise the successful candidate. The candidate will have the opportunity to work with unparalleled data and computational resources. Data resources include (a) Access to >10 million patient records in the Mount Sinai Data Warehouse with multi-modal data; (b) The Mount Sinai Million health Discoveries Program with >100,000 patients with whole exome sequencing data linked to longitudinal clinical data; (c) Ability to deploy the models into clinical care. He or she will have the opportunity to develop their own research projects and to lead or participate in local as well as international collaborations. As an advisor, Dr. Itan actively encourages the professional development of his lab members and facilitates presentation of exciting findings in pioneering conferences.

The postdoctoral fellow will join a dynamic team of data scientists, geneticists, and clinicians and participate in unique opportunities to apply cutting-edge computational and statistical techniques for important scientific breakthroughs and to directly impact patients’ lives in a clinical setting.

Qualifications

The ideal candidates will have the following background:

1. Ph.D., M.D., or equivalent doctorate in computational biology, human genetics, disease genomics, population genetics, bioinformatics, or a related field.

2. Proficiency in programming (e.g., Python) and statistical computing (e.g., R).

3. Excellent publication record.

4. Strong communication and presentation skills with fluency in spoken and written English.

Information on the Postdoctoral Training Program at Mount Sinai: http://icahn.mssm.edu/education/postdoctoral-training. To learn more about the Icahn School of Medicine at Mount Sinai: http://icahn.mssm.edu.Incoming postdoctoral fellows are eligible for affordable Mount Sinai Housing within walking distance of the medical school and of a wide range of amenities as well as visa sponsorship on a case-by-case basis.

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