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: [email protected]

Applications should be received by January 4th, 2021. To learn more about Computational Oncology, please visit: http://CompOncMSK.org 

 

Post-Doctoral Fellowship in Genetic Epidemiology and Computational Genomics

We seek a postdoctoral fellow in genetic epidemiology and computational genomics to join an expanding research group focused on understanding the molecular underpinnings of inherited cancer susceptibility. The fellow will lead analytical studies of germline susceptibility to esophageal adenocarcinoma and its precursor lesion Barrett’s esophagus, with a primary focus on statistical fine-mapping, single-cell sequencing analysis, and functional bioinformatics. As an active member of an interdisciplinary research group, the fellow will build relationships with a range of scientific colleagues, publish peer-reviewed work, present at national conferences, and gain experience in grant writing.

Qualifications and attributes of the ideal candidate include:

• A doctoral degree in biostatistics/bioinformatics, epidemiology, or related quantitative discipline.
• Peer-reviewed publications in genetic epidemiology, statistical genetics/genomics, or related fields.
• Interest in applying statistical and computational approaches to understand cancer susceptibility.
• Strong understanding of quantitative methods, study design, and data analysis and interpretation.
• Excellent coding skills in R and/or Python, and experience working on Linux-based clusters.
• Familiarity with public bioinformatics resources such as Roadmap/ENCODE, GTEx, TCGA.
• Self-motivated, resourceful, enthusiastic; solid verbal and written communication skills.

Interested applicants should send inquiries and applications to Dr. Matthew F. Buas ([email protected]), Associate Attending, Departments of Epidemiology/Biostatistics and Clinical Genetics. Please include a brief letter of interest, C.V., and contact information for three references.

 

Post-Doctoral Fellow in computational single-cell genomics

The newly formed Soldatov lab is seeking to recruit Postdoctoral Fellows to join us at Memorial Sloan Kettering Cancer Center (MSKCC) in New York. The lab is part of a dynamic and highly collaborative Computational Oncology Program, a significant new initiative in the field of Computational Oncology.   Motivated by new advances in machine learning and high-resolution sequencing and imaging technologies, the group is focused on important questions arising in understanding normal tissue function and disease dynamics of cancers. Successful candidates will drive key research questions that cross cut the themes of somatic evolution, regulation of cell fate decisions, and organization of the microenvironment. The projects will involve analysis of multi-omics, pooled perturbations and spatially-resolved datasets. The candidates will have an opportunity to focus on developing computational methods, work on ambitious collaborative projects and develop new projects. Lab website: https://componcmsk.org/quantitative-cell-dynamics-soldatov.

Positions are available for candidates who have or will soon have a PhD and a demonstrated track research record in the fields of functional genomics, transcriptomics, computational biology, bioinformatics or related discipline (computer science, physics, data science, statistics). Applications will be considered on scientific merit and we seek to support gender, racial, ethnic, and other underrepresented groups in biomedical sciences, including exceptional candidates for The Henry and Alexia Fernandez Computational Oncology Fellowship. MSK provides strong support for the development of postdocs, competitive salaries and benefits.

Click here to apply: https://careers.mskcc.org/vacancies/2023-66684-postdoctoral-fellow-in-c… 

 

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 analyzing high-dimensional flow cytometry data, single-cell RNA sequencing, multiplex imaging, and spatial transcriptomics in 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 single-cell data 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 ([email protected]): 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 cancer genomics, for a position as a postdoctoral fellow. This position will focus on developing statistical models and computational methods for the integration of data from multi-modal tumor-profiling (targeted, whole-exome, whole-genome sequencing, DNA methylation, RNA-seq, spatial transcriptomics), and working with a highly interdisciplinary group of investigators toward understanding cancer biology and disease progression.

 

The ideal candidate should have:

• PhD degree in biostatistics, statistics, bioinformatics, or a related field
• experience in NGS sequencing data analysis including whole-exomes and whole-genomes
• 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

 

Please send CV, a letter outlining your interest and names/contact information of three references via email to:

Samantha Vasquez

Assistant to the Chairman

[email protected]

 

Principal Biostatistician

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 [email protected].

 

Assistant Research Biostatistician

A position is available for an Assistant Research Biostatistician in the team of Dr. Andrew Vickers in the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. You will engage in collaborative projects involving the design, analysis, and publication of research across a variety of fields in cancer research, including urology, surgery, anesthesia, clinical trials and patient-reported outcomes. Dr. Vickers has more than 20 years of experience in cancer research. He is well known for the statistical technique known as decision curve analysis and for his work on developing the 4Kscore, a test now widely used in prostate cancer. You will be joining a highly-productive team of 4 statisticians, nested within a larger team of 15 – 20 researchers

 

You have:

• A Master’s degree in biostatistics, applied statistics, or a related field

You are:

• Proficient in applying statistical methods to studies in humans
• Proficient in a statistical programming language, preferably R
• Able to effectively communicate scientific ideas, methods, and results
• Passionately committed to using clinically-relevant statistics to improve human health

If interested, send a cover letter and resume to Andrew Vickers at [email protected]. 

 

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.

 

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.