Computational oncology postdoctoral fellowship with Pedram Razavi, MD, PhD, MSK Biomarker Development Program
Memorial Sloan Kettering Cancer Center
Location: New York, New York
Academic / Research
Internal Number: 64764
Memorial Sloan Kettering Cancer Center (MSK) is one of the world's premier cancer centers, committed to exceptional patient care, leading-edge research, and superb educational programs. The blending of research with patient care is at the heart of everything we do. The institution is a comprehensive cancer center whose purposes are the treatment and control of cancer, the advancement of biomedical knowledge through laboratory and clinical research, and the training of scientists, physicians and other health care workers.
We are currently looking for highly motivated postdoctoral fellows to join Dr. Pedram Razavi's team within the MSK Biomarker Development Program (BDP) focused on liquid biopsy technology development and Multi-Omics approaches. Dr. Razavi's research focuses on the discovery of novel biomarkers for the early diagnosis and predictors of recurrence in breast cancer. Our team applies an integration of large-scale data from genomics and transcriptomic methods and pathology tools, to understand the tumor evolution in breast cancer and response to therapy.
Fellows will join a multidisciplinary group of bioinformaticians, medical oncologists, molecular biologists, and clinical researchers to develop novel approaches for the analysis of cell free DNA (cfDNA) and breast cancer tissues. Fellows will apply novel analytic methods on a combination of newly generated and public big data to address high clinical impact questions to advance the ability to treat cancer patients.
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, Matlab,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.
Please send CV, a letter outlining your interest and names/contact information of three references via email to:
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.