New York, NY, USA
259 days ago
Postdoctoral Fellow, Computational & Systems Biology – Dey Lab at Memorial Sloan Kettering Cancer Center
Postdoctoral Fellow, Computational & Systems Biology – Dey Lab at Memorial Sloan Kettering Cancer Center Job Locations USA-NY-New York Posted Date 11 months ago(9/6/2023 10:06 PM) Requisition ID 2023-72162 Category Post-Doctoral Pay Range $55,439 – $100,940 Pay Range $55,439 – $100,940 Company Overview

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. 

 

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Job Description

The Dey Lab in Computational & Systems Biology program at Memorial Sloan Kattering Cancer Center is seeking a postdoctoral fellow to lead inter-disciplinary collaborative projects jointly supervised by Dr. Dey and Dr. Gao Wang, Assistant Professor of Neurological Sciences, Columbia University, Department of Neurology (https://www.neurology.columbia.edu/profile/gao-wang-phd). The candidate will work to  

 

--Develop new methods in statistical genetics and machine learning/generative AI for integrating multimodal omics data (RNA-seq, ChiP-seq, ATAC-seq, Perturb-seq) with GWAS data to inform fine-mapping and polygenic risk score (PRS) predictions. 

--Develop new strategies for improving the transferability of the PRS across diverse ancestries using a combination of genetic data from diverse ancestries (AllofUS, MVP, UKBB).  

--Develop and apply integrative statistical/ML models to identify disease sub-phenotypes and perform patient risk stratification using multimodal data from Alzheimer's’ patients as part of the ADSP project and different cancer types as part of the MSKCC sequencing cohort.  

  

We welcome applications from candidates with an exceedingly strong quantitative background in statistics, biostatistics, computer science, or other related domains. The applicant would be required to have prior experience working with large-scale genetic and omics data, resulting in a high quality first/co-first author publication. The candidate must be proficient in computing, with expertise in R and/or Python. Prior background in machine learning or generative AI models will be a plus, but not required.  

 

The candidate’s primary affiliation will be through the Sloan Kettering Institute, MSKCC located on the Upper East Side of New York City. It is part of the vibrant Tri-Institutional Research campus adjacent to Rockefeller University and Weill Cornell Medical College. Sloan Kettering offers competitive postdoc salaries and convenient subsidized housing. The candidate will have office space in both the Computational and Systems Biology Program, MSKCC and Department of Neurology, Columbia University. The candidate will have weekly meetings with both Dr. Dey and Dr. Wang and will be working closely with collaborators from various consortia like ADSP, ENCODE, and IGVF.  

  

To apply, please send a CV, a brief cover letter outlining your interest, and names/contact information for three references to both the following email addresses: 

 

deyk@mskcc.org 

gw2411@cumc.columbia.edu 

 

Salary: $55,439 – 100,940 (depending on postgraduate experience) 

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MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status, or any other factor which cannot lawfully be used as a basis for an employment decision.  

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