Applications for GEMS Summer 2024 are now open
Program Overview
Genomics Experience for Master’s Students (GEMS) is a 12-week program for master’s level quantitative scientists that aims to create an immersive experience for the student to engage in real-world team science projects and learn to apply and translate their quantitative skills into meaningful scientific contributions in cancer medicine with a focus on cancer genomics and precision oncology. This full-time, on campus research experience allows students to fully engage with mentors and a multidisciplinary research team on cutting-edge projects with the goal to propel them into genomics-oriented data science careers. Each fellow will have two mentors – one quantitative/computational mentor and one scientific mentor – to provide a highly interdisciplinary and immersive training environment and will prepare students for the interdisciplinary translational science workforce. Trainees must demonstrate a strong interest to learn cancer genomics and need not have experience in this area.
Program Goal
Through this immersive 12-week experience, fellows will gain:
- Perspective on modern frontiers in cancer genomics research
- Exposure to modern foundational concepts and methods taught through the seminar series
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Knowledge of foundational concepts and methodology including:
- how to process and manipulate large multi-dimensional data
- methods for data normalization, dimension reduction
- detection and correction for batch effects
- software and tools for data visualization
- basic strategies for integrative analysis of multidimensional and multimodal data
- Education in the responsible conduct of research
- Training in effective scientific communication
- Experience in critical thinking, problem solving, and teamwork through the dual-mentorship model embedded in a multidisciplinary scientific team.
Important Information
Accepted fellows will be paid a modest stipend. Housing is not provided, but GEMS will provide a nominal payment for housing expenses. A portion of fellow travel to and from New York City is eligible for reimbursement.
Applications for Summer 2024 are open and will close 5 p.m. (Eastern time) on Tuesday, January 16th, 2024.
The Summer 2024 program will run from May 20th to August 9th.
Eligibility Criteria
Eligible applicants must be:
- Currently matriculated in a master level program (biostatistics, statistics or related field)
- Trained in statistical theory, methods and programming and related fields
Application Requirements
- Resume
- Statement of interest (~500 words)
- Three letters of recommendation
Internship Location
The GEMS program is housed within Memorial Sloan Kettering’s Department of Epidemiology and Biostatistics, located in midtown Manhattan. The Department’s offices at 633 3rd Avenue are in easy walking distance of several New York City subway lines and the Metro North Railroad at Grand Central Terminal. Penn Station (Long Island Railroad, New Jersey Transit) and the Port Authority Bus Terminal are easily accessible via mass transit. MSK operates regular shuttle buses between midtown and MSK’s main campus on the Upper East Side, where GEMS fellows will have access to the MSK Library and to relevant lectures, seminars, and other educational activities.
Research Areas
Proposed projects will apply statistical and computational methods in areas including:
- Precision oncology approaches to optimizing cancer therapy and patient response
- Impact of mutational processes on immuno-suppression and evasion
- Single cell transcriptomics profiling for cancer immunotherapy
- Multi-omic characterization of cancer genomes and racial disparities
- Data science approaches to derive real-world evidence in oncology with integrated genomic and electronic health records data
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.