The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. One of the world’s most respected comprehensive centers devoted exclusively to cancer, we have been recognized as one of the top two cancer hospitals in the country by U.S. News & World Report for more than 30 years.
Job DescriptionExciting Opportunity at MSK: Faculty Position in Computational Oncology
The Computational Oncology Program at Memorial Sloan Kettering Cancer Center (MSK) is inviting applications for tenure track faculty positions. We are seeking exceptional candidates to join our faculty and develop independent investigator-led, computationally-focused cancer research programs. The Computational Oncology Program at MSK has grown to eleven faculty members who have created a vibrant, dynamic, and collaborative scientific community in the field of computational oncology. Successful candidates will join this community and will be supported to develop world-leading independent scientific programs to advance our understanding of cancer biology. Newly appointed faculty will be expected to conduct next generation translational research focused on cancer and driven by data science, artificial intelligence, machine learning, computer science, computational biology, and other quantitative fields. You will have the opportunity to collaborate with exceptional clinician-scientists, generate unique experimental data, analyze unique and best in class real-world datasets and to study biospecimens derived from the MSK patient population. In addition, successful candidates will join the newly formed Halvorsen Center for Computational Oncology.
Focus Areas:
Single cell dynamics and spatial biology of tumors Anti-tumor immunity and immuno-oncology Drug sensitivity and resistance mechanisms Artificial intelligence and analysis of real world & clinical data from patients including computational pathology, medical imaging and large language models for EHRs Multimodal data integration (e.g. genomics with clinical data & pathology images or multi-omic integration) Computational method development for any of the above areas Other emerging areas in cancer research
Key Qualifications:
MD, MD/PhD in Bioinformatics, Computational Biology, Computer Science, Mathematics, Statistics or a related discipline.Strong backgrounds in machine learning/AI, algorithm development, mathematical modeling, data science or data-driven discovery.Pay Range $150,000-$400,000
Physician compensation is based on multiple variables. This range represents annual salary only and does not include supplemental performance-based pay or any one-time payments that eligible candidates may be offered at the time of hire.
Application Instructions:
Submit your cover letter, curriculum vitae, a summary of current and proposed research programs, and arrange for three letters of recommendation to:
Dr. Sohrab Shah, Chief of Computational Oncology, c/o Cristina Radu, Memorial Sloan Kettering Cancer Center,
321 East 61st Street 4th floor, New York, NY 10065; E-mail: CompOncBST@mskcc.org.
Applications should be received by 12/01/2024. To learn more about recent advances from our Computational Oncology labs, please visit: http://CompOncMSK.org/news.
Helpful Links:
MSK Compensation PhilosophyReview Our Greats Benefits Offerin ClosingMSK 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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