Memorial Sloan-Kettering Cancer Center Computational Biologist Sr II in New York, New York
Computational Biologist Sr II
Job Posting Number: 22920
Allied Health – Biomedical Engineering
July 10, 2018
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.
The mission of the Marie-Josée and Henry R. Kravis Center for Molecular Oncology (CMO) is to promote precision oncology by using genomic analysis to guide the diagnosis and treatment of cancer patients. The CMO brings together clinicians and scientists throughout MSKCC to conduct large-scale translational research involving molecular characterization of patient tumor specimens in order to understand correlations between genomic features and clinical outcomes.
The Innovation Laboratory within the CMO is a group of experimental and computational scientists dedicated to the creation and optimization of genomic assays for near-term clinical use. Active areas of research include ultra-deep sequencing of circulating cell-free DNA from plasma and other bodily fluids, optimization of DNA and RNA capture techniques, molecular profiling of challenging clinical samples (FFPE tissue, small biopsies, cytological specimens), integration of somatic and germline genomics, novel biomarker discovery, and single-cell genomics applications. The goals of the Innovation Laboratory are 1) to develop and validate genomic assays and associated computational pipelines for the molecular characterization of human tumors, 2) to evaluate emerging technologies for potential clinical utility, 3) to pilot new technologies in collaboration with clinical and translational investigators, and 4) to work with clinical laboratories to ensure quality standards mandated by CLIA. New clinical assays will be deployed both retrospectively to discover biomarkers that track with therapeutic response, and prospectively to inform treatment decisions and guide patients to promising clinical trials.
The Innovation Laboratory is searching for outstanding computational and data scientists with a strong interest in developing and applying bioinformatic/quantitative methods to problems in translational cancer biology. The candidate should have a solid background in both bioinformatics and cancer biology and an interest in machine-learning and data science-focused methodologies to lead in the development of state-of-the-art genomics and multi-omics analysis platforms. The candidate will interact with investigators with expertise in computational biology, translational therapeutics, and molecular pathology among others. The ideal candidate will have a focus on and dedication to translational science, be an innovative thinker, exceptional communicator, enjoy working with an interdisciplinary team, and bring intellectual and analytical rigor to their work.
Capable of building strong collaborative relationships and working with others to meet shared objectives and goals
A good decision-maker, with proven success at making timely decisions that keep the organization moving forward
Effective at working when presented with complex, and sometimes contradictory, information
Able to consistently achieve results, even during high-pressure circumstances
Organized and can prioritize work to meet commitments aligned with organizational priorities
An effective communicator, capable of determining how best to reach different audiences and executing communications based on that understanding
Able to recover from setbacks and skilled at finding detours around obstacles
A quick learner, and able to apply insights from past efforts to new situations
Work in concert with the group leader and the Innovation team to provide support to research projects at the Center
Design, develop, and implement software tools for processing and analyzing high-throughput next-generation sequencing data
Provide one-on-one consultation and training to research scientists, bioinformatics scientists, and software engineers at the Center in the use of bioinformatics software tools and databases
Be responsible for conducting independent analysis and interpretation of genomic and other multi-omic data generated by the group
Help facilitate collaborations and research opportunities with scientists and clinicians at MSK
A PhD degree (strongly preferred) with 2-4 years of experience or a Master’s degree with 4-7 years of experience in biological science, physics, applied mathematics, computer science, bioinformatics, or a related field
Solid programming skills and proficiency with scientific computing software (Matlab, R) and scripting languages – a thorough understanding and experience in statistics is strongly preferred
Experience in statistical genetics/genomics and a familiarity with next-generation sequence data and analysis tools – extensive research experience in the biological sciences is strongly preferred
To be able to work both independently and collaboratively and make necessary connections with experts in various biological and clinical groups
To be highly motivated with excellent oral and written English communication skills – experience in delivering oral scientific presentations and writing scientific articles is strongly preferred
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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