For Current QBS PhD Students:
Upon review, QBS PhD students who have completed all of their required coursework may be awarded a Master’s in QBS in situations where they do not successfully advance to PhD candidacy or if they choose to separate from the program.
For Current Non-QBS PhD Students:
The internal Master's in QBS degree is offered to current doctoral students at Dartmouth who are enrolled full time in a PhD program other than QBS. Students must be in good standing to apply and have the approval of both their advisor and program. Eligible PhD students must meet the following requirements between the start of their undergraduate degree and the submission of their application:
- 1 course in calculus
- 1 course in statistics or equivalent experience
- 1 course in programming or equivalent experience
Prior to applying, interested students are encouraged to contact Kristine Giffin, PhD, Director of Academic and Student Affairs (Kristine.A.Giffin@Dartmouth.edu) to review the degree requirements and application process.
Applying to the Internal Master’s in in QBS
Applications must be submitted directly through the Dartmouth online application system by the published deadline. For access to the application portal, please contact Kristine Giffin, PhD, Director of Academic and Student Affairs (Kristine.A.Giffin@Dartmouth.edu).
Application Deadline: December 1, 2025
Required Material:
- A signed letter of approval to apply to the program from both the student’s advisor and their program (director, chair or administrator) that states the following:
- That the student is in good academic standing
- That have reviewed required coursework
- That they grant their approval to apply to and complete the program
- An updated Dartmouth transcript
Tuition and Funding
Students accepted to the program are provided a full tuition scholarship and incur no additional costs to complete the degree.
Degree Requirements
The MS in QBS degree is earned by completing 6 units of required core courses and 2 units of approved electives. No final dissertation is required. Upon completion, the degree may be conferred during any quarter of the student’s PhD candidacy, but no later than the final quarter of their dissertation defense. Since many QBS courses are open to students in other programs and departments, interested students may begin to fulfill degree requirements prior to being accepted. Credit will be given for any required course with a grade of “Pass” or higher that does not already count towards that student's PhD program requirements. Intent to apply should be made known to their advisor, their program, and the QBS administration before they enroll in more than 3 QBS courses that are eligible to count towards the MS degree.
Course Requirements
Core Courses
6 units from the following core courses with at least 1 unit in each area
Bioinformatics
- Students without bioinformatics backgrounds are encouraged to enroll in QBS 146, which looks broadly at computational tools and bioinformatic applications. Those with advanced bioinformatics experience can alternatively enroll in Introduction to Statistical Genetics, QBS 148.
- QBS 146 Foundations of Bioinformatics I
- QBS 145 Computational Immunology
- QBS 148 Introduction to Statistical Genetics
Biostatistics
- The QBS biostatistics curriculum is designed to start with either 119 or 120 in the Fall term followed by 121 in Winter. After 121, students will have sufficient background for the later QBS biostatistics and machine learning courses (108, 122, 124, 126, 177). However, students are encouraged to take 120 vs. 119 if they want to enroll in QBS 122 or 124, given the more mathematical/theoretical nature of these classes. Students who have recently taken a graduate-level equivalent to 119/120 or 121 may opt to skip these classes and directly enroll in more advanced courses (permission of the advanced course instructor is required).
- QBS 108 Machine Learning
- QBS 119 Foundations of Biostatistics I: Applied Biostatistics
- QBS 120 Foundations of Biostatistics I: Statistical Theory for the Quantitative Biomedical Sciences
- QBS 121 Foundations of Biostatistics II: Regression Modeling
- QBS 122 Foundations of Biostatistics III: Modeling Complex Data
- QBS 124 Advanced Biomedical Data Analysis
- QBS 126 Analysis of Densely Collected Longitudinal Data
- QBS 177 Methods of Statistical Learning for Big Data
Epidemiology
- Students who have never taken a graduate-level course in epidemiology should first take QBS 130. Students who have taken 130 or equivalent may take 131, 132, 133, 136 and/or 137. 136 and 137 should not be the only epidemiology coursework taken to meet core course requirements.
- QBS 130 Foundations of Epidemiology I: Theory and Methods
- QBS 131 Foundations of Epidemiology II: Theory and Methods
- QBS 132 Molecular Biologic Markers in Human Health Studies
- QBS 133 Clinical Epidemiology
- QBS 136 Applied Epidemiological Methods (0.5 unit)
- QBS 137 Applied Epidemiological Methods II (0.5 unit)
Electives Courses
Choose 2 units from this list. Students may petition to receive credit for electives not found on this list. For more information contact (Kristine.A.Giffin@dartmout.edu)
- QBS 101 Foundations of Programming for Data Scientists
- QBS 101.1 Intermediate Programming (winter)
- QBS 103 Foundations of Data Science
- QBS 108 Applied Machine Learning
- QBS 119 Foundations of Biostatistics I: Applied Biostatistics
- QBS 120 Foundations of Biostatistics I: Statistical Theory for the Quantitative Biomedical Sciences
- QBS 121 Foundations of Biostatistics II: Regression Modeling
- QBS 122 Biostatistics III: Modeling Complex Data
- QBS 123 Biostatistics Consulting Lab (0.5 unit)
- QBS 124 Advanced Biomedical Data Analysis
- QBS 126 Analysis of Densely Collected Longitudinal Data
- QBS 130 Foundations of Epidemiology I: Theory and Methods
- QBS 131 Foundations of Epidemiology II: Theory and Methods
- QBS 132 Molecular Biologic Markers in Human Health Studies
- QBS 133 Clinical Epidemiology
- QBS 136 Applied Epidemiological Methods I (0.5 unit)
- QBS 137 Applied Epidemiological Methods II (0.5 unit)
- QBS 139 Advanced Methods in Health Services Research
- QBS 140 Decision & Cost-Effective Analysis
- QBS 145 Computational Immunology
- QBS 146 Foundations of Bioinformatics I
- QBS 147 Genomics: From Data to Analysis
- QBS 148 Introduction to Statistical Genetics
- QBS 177 Methods of Statistical Learning for Big Data
- QBS 180 Data Visualization (0.5 unit)
- QBS 181 Data Wrangling
- QBS 192 Health Informatics
- QBS 195 Independent Study
Additional Information:
Application Review Process:
Applications are reviewed by the QBS Director and the QBS Director of Academic and student affairs for program acceptance. Offers will be sent to applicants before January1
Admitted Applicants:
After accepting the offer to join the MS in QBS degree program, students will meet with the Director of Academic and Student affairs to review their outstanding degree requirements.
Grade Standards
The following statements describe the policies and procedures that apply to students whose academic performance is unsatisfactory.
Grades of LP or NC in core courses have serious consequences. Students who receive more than one NC, or more than two LPs, during one term or over multiple terms, may be suspended or dismissed from the program after an assessment hearing by the QBS Advisory Committee.
Unless otherwise approved by the QBS Advisory Committee, students cannot graduate with 3 or more LPs on their transcripts without retaking one or more of those courses, regardless of the number of units that course holds. If a student retakes a course and receives a second LP or NC, the student may be dismissed from the program.