Computational oncology postdoctoral fellows - MSK Biomarker Development Program
Memorial Sloan Kettering Cancer Center
Location: New York, New York
Academic / Research
Internal Number: 65386
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. One of the world's most respected comprehensive centers devoted exclusively to cancer, we have been recognized as one of the top two cancer hospitals in the country by U.S. News & World Report for more than 30 years.
In compliance with applicable State regulatory authorities, vaccination for COVID-19 and Influenza (flu) is mandatory for all MSK staff who do not work 100% remotely (including new hires ). Staff are considered fully vaccinated upon completion of a primary vaccination series for COVID-19 Exceptions from the COVID-19 vaccine requirement are permitted for those who request and receive an approved medical, religious, or fully remote exemption. Requests for exemption can take up to two weeks to review. Vaccination or an approved medical exemption is required to start work.
We are currently looking for two highly motivated postdoctoral fellows to join the liquid biopsy and cancer genomics programs (led by Dr Pedram Razavi) within the MSK Biomarker Development Program (BDP). The MSK BDP is a dedicated program focused on development and utilization of tumor tissue and circulating biomarkers to enable precision oncology and inform therapeutic decisions.
Research in the Razavi group focuses on integration of large-scale tissue and circulating genomics with clinicopathologic data to study tumor evolution under therapeutic pressure in breast cancer, discover novel biomarkers of response or resistance to therapies in breast cancer and develop tools for early detection and prediction of outcomes in breast cancer.
Fellows will join a multidisciplinary group of bioinformaticians, translational medical oncologists, molecular biologists, pathologists and clinical researchers focusing on two main studies: 1) analysis of the largest effort to date in breast cancer focusing on comprehensive genomic profiling of paired pre- and post-treatment tumor tissue to decipher the mechanisms of resistance to adjuvant therapies in breast cancer and develop prediction models of outcomes in breast cancer; and 2) development of novel approaches for the analysis of cell free DNA (cfDNA) to assess cfDNA utility in a wide array of practical clinical applications such tumor genomic profiling, monitoring disease evolution and heterogeneity, discovery of novel mechanisms of therapy resistance, detection of minimal residual and micrometastatic disease, and early- detection of disease. Fellows will apply analytic methods on a combination of newly generated and big data to address high clinical impact questions to advance the ability to treat cancer patients. There will be several opportunities for co-mentorship by collaborators across departments and services at MSK.
A PhD in a quantitative discipline, including but not limited to computational biology, computer science, machine learning, or applied mathematics.
Experience in massively parallel sequencing data analysis, and understanding of genetics and genomics, including epigenomics, transcriptomics, disease genomics and statistical genetics.
Strong background in machine learning/AI, algorithm development and mathematical modeling applied to the biomedical research field. Knowledge of ctDNA analysis is an asset but not required.
Demonstrated experience with several programming languages: R, Python, Java, Unix
Excellent communication skills, and ability to work independently and as part of a team.
We are seeking candidates to develop computational methods and applied translational data analysis in cancer biology and clinical care. Some of the key responsibilities are:
Analysis of high-throughput sequencing data of tumors in the contexts of drug response, modeling clonal evolution and the tumor microenvironment.
Multimodal data integration of clinical data with advanced molecular approaches such as genomics, spatial transcriptomics, proteomics, radiological and histological imagining.
Cancer genomics including germline and somatic genetics, mutational processes, and genomic instability.
Longitudinal analysis of timeseries data from cfDNA sequencing.
If you have any questions about this job opportunity, please contact:
Program administrator for the BDP
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At Memorial Sloan Kettering (MSK), we’re not only changing the way we treat cancer, but also the way the world thinks about it. By working together and pushing forward with innovation and discovery, we’re driving excellence and improving outcomes. For the 28th year, MSK has been named a top hospital for cancer by U.S. News & World Report. We are proud to be on Becker’s Healthcare list as one of the 150 Great Places to Work in Healthcare in 2018, as well as one of Glassdoor’s Employees’ Choice Best Place to Work for 2018. We’re treating cancer, one patient at a time. Join us and make a difference every day.