Company Overview

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.

Job Description

Are you a machine learning / artificial intelligence scientist who strives to tackle the major contemporary challenges facing cancer research scientists and clinicians? Memorial Sloan Kettering Cancer Center (MSK) has initiated a unique and transformative data-driven research endeavor to unlock features in imaging, molecular and clinical data that will better predict patient outcomes and ultimately be translated to improved patient care. Simultaneously, this program will create a data platform for large-scale multi-modal data integration and research. As a significant component of cancer research has firmly moved into the realm of the quantitative sciences, interdisciplinary collaborations between clinicians, molecular biologists and you now underpin modern scientific advances. MSK Mind a new and prestigious career development opportunity[1] is recruiting exceptional data and computational scientists to develop and apply contemporary computing techniques that will synthesize high dimensional and disparate measurements of the complex biological system that is a cancer.

Join our team at MSK and embrace the opportunity to tackle new analytical challenges with unprecedented high volume clinically annotated complex and multi-modal datasets, while impacting health care with advances for cancer patients. Our initial program is targeting lung, breast, colorectal and ovarian cancer, synthesize and perform biomarker discovery using data from thousands of highly curated and annotated clinical records linking to our vast genome sequencing (MSK-Impact), digital pathology and radiology image archives.

Aligned with MSK’s core mission of “To lead in the prevention, diagnosis, treatment, and cure of cancer through programs of excellence in research, education, outreach, and cost-effective patient care”, the MSK MIND initiative will advance excellence in computational research within the MSK data ecosystem to drive discovery. MSK MIND is a new division of Computational Oncology and is searching for talented self-driven computational and statistical scientists (MSK MIND Scholars) to propel in-depth integrative analysis of multiple radiologic, histologic, genomic, molecular and clinical information derived from the MSK patient population. She/he will also develop and implement machine learning and AI-driven analysis frameworks and statistical tools to be utilized more broadly across a range of project goals in the institution.

Activities of the MSK MIND Scholars:

• Develop and/or apply novel research methodology to perform feature extraction, multi-sensor data fusion and clustering and classification on imaging, genomic and clinical data sets at scale.
• Collaborate with clinical and biological scientists to advance and execute hypothesis driven research
• Collaborate with data engineers to design, develop, and implement software and database solutions optimized for discovery-based research
• Optionally write and prepare scientific manuscripts for publication in journals and conferences
• Participate in fostering a new branch of academic research in Computational Oncology at MSK through journal clubs, work in progress sessions and mentoring of graduate students
• Collaborate with academic partners at other institutions
• Liaise with and collaborate with industry partners in biotech, health data, and big tech

You Are:

• A science-focused individual with motivation and track record of advancing computational and/or domain specific research questions
• Attracted to large-scale data sets and quantitatively driven solutions and conclusions
• Interested in methodology for analysis of complex multi-modal data sets
• A strong communicator and collaborator with a team-oriented mindset required to effectively collaborate with clinicians, biologists and engineers
• Able to work effectively in a dynamic environment and adapt to occasional shifts in priorities

You Need:

• Ph.D. in computer science, statistics, data science, engineering or equivalent
• Expert understanding of principles behind contemporary computational techniques such as deep learning (convolutional neural networks, mask R-CNN, etc..), transfer learning, variational autoencoders, Bayesian approaches, probabilistic graphical models, computational statistics
• Experience in at least one of: image analysis, genomic analysis, clinical and health data analysis, natural language processing, multisensor data fusion
• (Desired) experience in computing in data lake and cloud computing environments
• A track record of publication in conference proceedings or academic journals or equivalent track record in industry
• Specific skill sets: TensorFlow, PyTorch

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Closing

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.  

Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.