Faculty Position in Computational Oncology, Memorial Sloan Kettering Cancer Center
Faculty Positions in Computational Oncology, Memorial Sloan Kettering Cancer Center
The Computational Oncology Program at Memorial Sloan Kettering Cancer Center (MSK) is inviting applications for tenure track faculty positions at the level of Assistant and Associate Member. Cancer research has firmly moved towards quantitative and data driven science. Responding to this challenge, we are seeking exceptional early to mid-career candidates to develop independent research programs that will grow and advance computationally focused cancer research at MSK. We are seeking candidates to develop innovative research programs to drive computational methods development and applied translational data analysis in cancer biology and clinical care. For example:
- Single cell dynamics of tumors, covering the contexts of drug response, modeling clonal evolution and the tumor microenvironment. Interests in computational methods for single cell ‘omics, cellular imaging, spatial transcriptomics and proteomics
- AI and machine learning in oncology including multimodal data integration (e.g. genomics with clinical data), medical and cellular imaging, digital pathology
- Cancer genomics including clinical germline and somatic genetics, endogenous and exogenous mutational processes, structural variations and genomic instability
- Longitudinal analysis of timeseries data such as cell free DNA, laboratory medicine data, radiologic data
- The cancer microbiome
- Drug sensitivity and resistance mechanisms
- Other emerging areas in cancer research
Eligible candidates will have a PhD in Bioinformatics, Computational Biology, Computer Science, Mathematics, Statistics or a related discipline. Candidates with strong backgrounds in machine learning/AI, algorithm development, mathematical modeling and/or data science and bioinformatics with proven publication track records in biomedical research and/or data-driven discovery are strongly encouraged to apply.
Our program is located at the newly created Computational Oncology Research Campus of MSK, encompassing the Computational Oncology research laboratories, and flanked by other computational groups such as clinical bioinformatics, radiology informatics, high performance computing, the Marie-Josée and Henry R. Kravis Center for Molecular Oncology (CMO) Computational Sciences and Technology Innovation groups. Our faculty develop fully independent computational research programs, collaborating extensively with clinical colleagues at MSK across all disease areas. Our faculty are eligible to hold appointments in the Gerstner Sloan-Kettering Graduate School of Biomedical Sciences, the Weill Cornell Medical College (WCMC) Graduate School and the Tri-Institutional Computational Biology for Medicine program across MSK and WCMC, providing access to exceptional graduate students.
We seek candidates committed to advancing equity, diversity, and inclusion (ED&I) in our research community. At MSK, diversity encompasses the variety of personal experiences, values and worldviews that result from differences in race, ethnicity, gender, age, religion, national origin, language, abilities/disabilities, sexual orientations, socioeconomic status, geographic region and more. Please in one page describe: What are your plans to promote diversity as a faculty member and a lab head in the future.
Please send curriculum vitae, a summary of current and proposed research programs, one page description on your plans to promote ED&I as a faculty member, and arrange for three letters of recommendation to be sent to: Dr. Sohrab Shah, Chief Computational Oncology, c/o Cristina Radu, Memorial Sloan Kettering Cancer Center, 321 East 61st Street 2nd floor, New York, NY 10065; E-mail: CompOncBST@mskcc.org.
Applications should be received by January 8th, 2022. To learn more about Computational Oncology, please visit: http://CompOncMSK.org.
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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