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  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 MSKs 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
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
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
Internal Number: 2019-36736
About Memorial Sloan-Kettering Cancer Center
As one of the world's premier cancer centers, Memorial Sloan-Kettering Cancer Center is committed to exceptional patient care, leading-edge research, and superb educational programs. The close collaboration between our physicians and scientists is one of our unique strengths, enabling us to provide patients with the best care available today as we work to discover more effective strategies to prevent, control, and ultimately cure cancer in the future. Our education programs train future physicians and scientists, and the knowledge and experience they gain at Memorial Sloan-Kettering has an impact on cancer treatment and the biomedical research agenda around the world.