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. 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. The MSK MIND AI Scientists are exceptional data and computational scientists to develop and apply contemporary computing techniques to 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, ovarian, blood, and pediatric cancer, synthesize and perform biomarker discovery and patient stratification using data from thousands of highly curated and annotated clinical records linking to our vast next-generation sequencing initiative (MSK-IMPACT), digital pathology, flow cytometry 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 to advance our research objectives.
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.
Advance and execute hypothesis driven research by collaborating with clinical and biological scientists.
Collaborate with data engineers to design, development, and implementation of open source software and data solutions optimized for discovery based research.
Write and prepare scientific manuscripts for publication in journals and present scientific results in 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.
Liaise with and collaborate with academic and 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 willing 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, bioinformatics, computational biology, engineering or equivalent
Expert understanding of principles behind contemporary computational and mathematical techniques such as deep learning for computer vision (image classification (e.g., CNN) and segmentation (e.g., Mask RCNN) algorithms ), variational autoencoders, Bayesian approaches, and probabilistic graphical models
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 big data infrastructure and cloud computing environments
A track record of publication in conference proceedings or academic journals or equivalent track record in industry
Programming skills, in particular Python and deep learning frameworks (e.g., PyTorch and TensorFlow)
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.