As a Postdoctoral Associate, you will be working on a project related to development of AI and machine learning (ML) models for deriving actionable insights from multimodal biomedical data, including clinical data, multi-omics, medical imaging. These insights will support downstream clinical and translational applications, such as disease risk prediction, characterization of disease heterogeneity and progression trajectories, and computational therapeutic discovery. You will be responsible for the following:
- Conduct the research independently and/or collaboratively with colleagues to ensure all method development, data analyses, and experiments are appropriately conducted following Lab, Department, and College policies and procedures.
- Develop and apply AI&ML methods for analyzing multimodal biomedical data such as clinical data (e.g., electronic health records [EHRs]), multi-omics (genomics, bulk transcriptomics, single-cell/spatial omics), medical imaging (e.g., MRI), etc.
- Interpret and evaluate the analysis results obtained from the AI/ML models.
- Collaborate closely with clinicians, biologists, and other collaborators to ensure the clinical and biological validity of the developed AI/ML models and analytical findings.
- Draft manuscripts on the conducted research and get them published on prestigious venues such as Nature, Science, Cell, and JAMA series.
- Present the research on academic conferences.
Minimum Qualifications:
The successful applicant should have obtained an MD or PhD degree within three years in health/biomedical informatics, bioinformatics, computer science, engineering, or a related field, with two letters of reference.
Preferred Qualifications:
The successful applicant should have a strong track record in developing AI/ML or advanced computational models in one or more of the following areas:
- Large-scale clinical data, such as electronic health records (EHRs) or insurance claims
- Large-scale multi-omics data, particularly single-cell and spatial omics
- Medical imaging, such as brain MRI or other biomedical imaging modalities
- Biomedical knowledge graphs, biological networks, or graph learning
- Multimodal foundation models for biomedical or healthcare applications
Application Process:
Interested applicants should submit, via email: (1) a cover letter describing their qualifications for and interest in the position; (2) a recent CV; and (3) the names and contact information of two references to Chang Su at chs4001@med.cornell.edu as soon as possible. Review of applications will begin immediately and will continue until the position is filled.
Appointment Term:
One year, with possible reappointment based on performance and funding availability
Starting Date:
We expect the successful candidate to start as soon as possible.
Location of Appointment:
The candidate is expected to work in-person at
6th Floor. 575 Lexington Ave. New York. NY 10022.
Lab and Department Websites:
PI homepage: http://www.chang-su.net and https://sites.google.com/view/changsu/home
Department website: https://phs.weill.cornell.edu/
Salary:
$80K-$90K
Benefits:
A summary of employee benefits can be found on the WCM Human Resources website.
Visa Options:
Candidates applying for this position could be eligible for a J-1 Exchange visitor visa and the H-1B temporary worker visa.
Union Membership:
This position is covered under a Collective Bargaining Agreement (CBA) between Weill Cornell Medicine and the International Union, United Automobile, Aerospace, and Agricultural Implement Workers of America (“UAW”), and its Local Union, Weill Cornell Medicine Postdocs United-UAW Local 4100.
Commitment to Diversity
Weill Cornell Medicine is committed to fostering a culture of diversity and inclusion among our faculty, staff, and students. We seek out individuals with a diverse range of backgrounds and experiences, and we work to create programs that support both our current employees and our recruitment efforts.
EEO Statement
Weill Cornell Medicine welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world-class education and career opportunities, to further the founding principle of “any person, any study.” No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.