Quantitative Sciences Undergraduate Research Experience (QSURE)

Quantitative Sciences Undergraduate Research Experience (QSURE)


QSURE Banner

Program Overview

The QSURE internship program is designed for exceptional undergraduate students with an aptitude in quantitative sciences and an interest in cancer and population health.  Students will participate in an individual research program and receive exposure to methods in biostatistics, epidemiology and health outcomes research. QSURE is funded by a grant from the National Cancer Institute (R25 CA214255).

Program Goal

The QSURE program aims to provide a hands-on research experience to undergraduates with an aptitude for and interest in quantitative sciences in cancer. By conducting research in biostatistics, epidemiology or health outcomes research, students will advance their quantitative skills and knowledge, as well as their understanding of options for graduate study and careers in these areas.

Important Dates

January 17th – Complete applications are due

February 7th – Notification of admission

June 1st – Start of QSURE

July 22-23rd – Final student presentations

August 7th – End of QSURE

Eligibility Criteria

Eligible applicants must:

  • Be enrolled as a full-time undergrad student with an expected graduation after December 2019
  • Be authorized to work in the US
  • Have at least one semester of college statistics (AP statistics courses do not count)
  • Be in good academic standing

Competitive Applicants Will Have

  • A keen interest in cancer and population health
  • Experience or aptitude in data analysis
  • A strong academic record
  • Excellent oral and written communication skills

Application Requirements

  • Resume
  • Statement of interest (~ 500 words)
  • Letter of good academic standing from Dean, College Counselor or equivalent
  • Letter of recommendation from Professor or equivalent 

After the Program Directors conduct the first review of applications and make preliminary recommendations for admission, each faculty mentor reviews the suggested pool and selects the applicant that best matches their planned project. Attributes of successful applicants include:

  • Demonstration of a desire to pursue graduate education or a career in quantitative sciences in health (e.g., statistics, biostatistics, epidemiology, health policy, behavioral sciences)
  • Motivation and aptitude for independent and collaborative research
  • Inquisitive mind
  • Commitment to professional conduct and integrity
  • Interests that align with an available project

  • A modest stipend will be provided
  • Applicants must be authorized to work in the US
  • Housing is not provided

The QSURE Internship is sponsored by Memorial Sloan Kettering’s Department of Epidemiology and Biostatistics, located in midtown Manhattan. The Department’s offices at 485 Lexington 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 QSURE interns will have access to the MSK Library and to relevant lectures, seminars, and other educational activities.

Student research projects vary from year to year, but all involve learning and using quantitative methods in Biostatistics, Epidemiology or Health Outcomes Research. Common research areas and methods include:

  • Survival analysis
  • Prediction modeling
  • Clinical trial design
  • Cancer epidemiology
  • Cancer genetics and genomics
  • Comparative effectiveness research
  • Quality and cost of cancer care
  • Late and long-term side effects in cancer survivors
  • Disparities in cancer care and outcomes

Accuracy of self-reported cigarette smoking in bladder cancer patients

The student quantified the difference in smoking patterns as reported by patients versus lab-confirmed values, and identified characteristics associated with patient misreporting. The results were presented at the American Urological Association Annual meeting.

Distribution of clinical features in patients receiving surgery for suspected renal cancer

The student analyzed the distribution of features (from tumor samples) and patient characteristics associated with a diagnosis of renal cancer.

Patterns of follow-up after treatment for early-stage breast cancer

The student summarized the types of follow-up received by patients after breast cancer treatment and identified characteristics related to discontinuation of follow-up.

The role of mobile facilities in access to screening mammography

The student expanded an existing database of all US screening mammography facilities by collecting data from different sources and analyzed differences between mobile and fixed facilities in terms of the populations they serve. The results were presented at the Esri Health GIS Conference.

Statistical methods for evaluating gene-environment interactions in case-control studies

The student examined statistical methods for evaluating interactions between a genetic factor and environmental exposure. These concepts were applied to an epidemiologic study on the risk of skin cancer based on sun exposure among people with or without the MC1R gene. The results were presented at the Annual Biomedical Research Conference for Minority Students.

Linear regression and the Box-Cox transformation

The student applied linear regression techniques with Box-Cox transformation to analyze continuous outcomes from a study of Nevi (a type of mole on the skin) in children.


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.