The Department is always growing and expanding. Below are some of the open positions in the department with descriptions and methods of applying.
For staff positions, please explore http://careers.mskcc.org/.
Faculty Positions in Computational Oncology
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
This year, MSK is conducting a search for two positions - one with a specific focus in computational pathology, to be recruited jointly with the Warren Alpert Center for Digital and Computational Pathology in the Department of Pathology.
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 diversity, equity and inclusion (DEI) 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 DEI 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 4th, 2021. To learn more about Computational Oncology, please visit: http://CompOncMSK.org
Post Doctoral Fellowship in Medical Physics/Biostatistics
We are seeking a highly motivated candidate, interested in biostatistics and bioinformatics, for a position as a postdoctoral fellow. This position will focus on machine learning-based modeling of outcomes on genome-wide association studies (GWAS) that include radiation and genetics (e.g., the Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study and REQUITE Study).
The ideal candidate should have:
- PhD degree in bioinformatics, computer science, biostatistics, statistics, physics or a related field
- Experience in predictive modeling using machine learning techniques
- Experience in analyzing large data sets, be proficient in at least one of the statistical programming languages R/Matlab/Python and have experience working on Unix/Linux systems and basic shell scripting
Experience in GWAS data analysis would be advantageous, but is not necessary.
Please send CV, a letter outlining your interest and names/contact information of three references via email to:
Jung Hun Oh, PhD
Assistant Attending, Department of Medical Physics
Faculty Position in Epidemiology
The Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center has an active research program encompassing multiple domains of cancer population science research. We invite applications from investigators seeking to build or further develop a program of independent research. The successful candidate will join our existing group of scientists engaged in research on cancer risk, cancer prevention, cancer survivorship and health services research. The MSK environment provides exceptional opportunities for fostering multi-disciplinary collaborations with clinicians, epidemiologists, geneticists, pathologists, biostatisticians, cancer biologists and others involved in cancer research. Our large patient population coupled with the extensive core facilities and distinguished research tradition provide a dynamic environment for the creation of an independent research program. Candidates should have a PhD in a field such as epidemiology, population science or health services research or an MD with masters training in epidemiology or a related discipline and must have suitable post-doctoral experience preparatory to a career as an independent research scientist. 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. Please send a CV, a letter outlining your interest in the position, a statement of your research ideas and the names and contact information of at least three references via email to:
Samantha Vasquez
Assistant to the Chairman
Principal Biostatistician
The Biostatistics Service, a group of 45 doctoral and MS-level biostatisticians, is seeking highly motivated and successful doctoral-level individuals to join them as a Principal Biostatistician.
You will:
- Participate in collaborative research between the Biostatistics Service and one or more of the clinical, translational, or basic science groups in the institution.
- Support clinical collaborators in the design of studies, analysis of data, and interpretation and communication of results.
- Act as either the lead statistician for a project or, depending on the nature of the project, collaborate with a team of biostatisticians.
You have:
- A doctoral degree in statistics, biostatistics, or a related field.
- Proficiency in a statistical programming language (such as SAS, Stata, or R).
- Experience with collaborative research (including creating and maintaining data files, analyzing data, interpreting results, and manuscript writing).
- Excellent verbal and written communication skills.
- A strong commitment to statistical collaborations with medical and basic science investigators.
- The ability to manage multiple projects, collaborations, and deadlines.
The department offers exciting opportunities for growth and development at all levels. The position is located in the heart of Manhattan, a vibrant, multi-cultural city that is home to world-class restaurants, museums, and theater. MSKCC offers comprehensive benefits for individuals and family members. Applicants with any level of experience are invited to apply.
Post Doctoral Fellowship in Biostatistics
We are seeking a highly motivated candidate, interested in clinical trial design, for a position as a postdoctoral fellow. This position will focus on design of cancer clinical trials in precision medicine and imaging with opportunities to work on methodological problems and design real clinical trials
The successful candidate should have solid methodological training in statistics, be comfortable developing simulations, and be proficient in R. Interest or expertise in Bayesian methods is preferred but not required. The successful applicant will be supervised by Dr. Mithat Gonen.
Applicants should hold a PhD degree in biostatistics, statistics or a related field. The successful candidate should have solid methodological training in statistics, be comfortable developing simulations, and be proficient in R. Interest or expertise in Bayesian methods is preferred but not required.
To apply, send a cover letter, CV, and the names of 3 references to Samantha Vasquez at vasques2@mskcc.org : Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017.
Post Doctoral Fellowship in Biostatistics
We are seeking a highly motivated candidate, interested in statistical and computational methods development and application in immuno-oncology studies, for a position as a postdoctoral fellow. This position will focus on multimodal integration of data including flow cytometry, single-cell RNA sequencing, and biomedical imaging in a large dataset of patients treated with immune checkpoint blockade (ICB) with rich clinical annotation. The candidate will have the opportunity to lead the development of novel statistical and computational approaches and work with world’s leading immuno-oncology experts.
Applicants should hold a Ph.D. degree in biostatistics, statistics, bioinformatics, or a related field, ideally with experience in high dimensional data analysis. The successful candidate should have solid methodological training in statistics, be comfortable working with large data sets, proficient in at least one of the statistical programming languages R/Matlab/Python and have experience working on Unix/Linux systems and basic shell scripting. Prior experience with either flow cytometry, CYTOF, single-cell RNA sequencing and/or imaging data analysis would be an asset.
The successful applicant will be supervised jointly by Drs. Ronglai Shen, Katherine Panageas and Margaret Callahan. To apply, send a cover letter, cv, and the names of 3 references to Ronglai Shen (shenr@mskcc.org): Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017.
MSKCC 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.
Post Doctoral Fellowship in Biostatistics
We seek an energetic and creative candidate, interested in reproducible analysis of biomedical data, for a postdoctoral fellowship position with Dr. Li-Xuan Qin at Memorial Sloan Kettering Cancer Center, New York. This position is to develop and apply statistical methods and software tools for analyzing high-dimensional data such as sequencing, with an emphasis on discerning the role that data preprocessing plays at the interface of method development and application. For example, transcriptomics data normalization may over-compress data variability and subsequently under-estimate the classification error based on cross-validation. In addition, this position offers ample opportunities for multi-disciplinary collaborations with the world’s leading oncology experts and for professional development including publication, presentation at scientific conferences, and involvement in grant writing.
Applicants should hold a PhD degree in biostatistics, statistics, or a related field, ideally with experience in high-dimensional data analysis. The successful candidate should have solid methodological training in statistics, be comfortable working with large data sets, be proficient in R, be organized and meticulous, and have strong verbal and written communication skills.
This position is open immediately until filled. To apply, email a cover letter, CV, and the names of 3 references to Li-Xuan Qin (https://www.mskcc.org/profile/li-xuan-qin) at qinl@mskcc.org, copying Samantha Vasquez at vasques2@mskcc.org.
Research Biostatistician
Research Biostatisticians work as members of a team of statisticians who are engaged in a wide variety of collaborative projects in clinical, laboratory and cancer prevention research (See Faculty Position in Biostatistics). A three level promotional track supports professional development which is fostered through direct supervision of work and regular participation in Service activities such as the Design Workshop, guest and faculty seminars, and the Journal Club. These positions require a Master’s degree in biostatistics or statistics, proficiency in statistical software packages, database manipulation, and good verbal and written communications skills.
If interested, please contact epibiostats@mskcc.org.
Research Assistant in Epidemiology
We are recruiting for a Research Assistant position in Epidemiology
As a Research Assistant you will assist in performing research activities in collaboration with internal/external personnel to complete science based projects. You will independently craft, plan, and develop new methods and technologies for project advancement. You will maintain a high level of expertise through familiarity with scientific literature and implement a quality assurance plan, as well as participate in scientific conferences and contribute to scientific journals.
Research Epidemiologist
Research Epidemiologists work as members of the Epidemiology group, engaged in studying the etiology of cancers, the genetic predisposition for cancers, and other avenues of prevention research (See Faculty Position, Epidemiology). A two level promotional track supports professional development which is fostered through direct supervision of work and regular participation in activities such as seminars, and the Epidemiology Journal Club. These positions require a Master’s degree in Epidemiology and/or Public Health, experience in statistical software packages, database manipulation, and good verbal and written communications skills.
Keep an eye on the page in the future for open positions.
Outcomes Research Epidemiologist
Outcomes Research Epidemiologists work as members of the Outcomes Research Group studying patterns and delivery of cancer treatments as well as the outcomes of these treatments. These positions require a Master’s degree in Epidemiology and/or Public Health, excellence in the analysis of data and writing of SAS queries and programs, experience with large database manipulations, and good verbal and written communications skills.
Keep an eye on the page in the future for open positions.
MSKCC 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.