).<\/span><\/p>\nApplication Deadline:<\/b> December 1, 2025\u00a0<\/span><\/p>\nRequired Material<\/b>:\u00a0<\/b><\/p>\n\n- A signed letter of approval to apply to the program from both the student\u2019s advisor and their program (director, chair or administrator) that states the following:<\/span>\n
\n- That the student is in good academic standing<\/span><\/li>\n
- That\u00a0 have reviewed required coursework\u00a0<\/span><\/li>\n
- That they grant their approval to apply to and complete the program<\/span><\/li>\n<\/ul>\n<\/li>\n
- An updated Dartmouth transcript<\/span><\/li>\n<\/ul>\n
<\/p>\n
Tuition and Funding<\/b><\/h2>\n
Students accepted to the program are provided a full tuition scholarship and incur no additional costs to complete the degree.<\/span><\/p>\n <\/p>\n
Degree Requirements\u00a0<\/b><\/h2>\n
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\u2019s PhD candidacy, but<\/span> no later<\/span> 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 \u201cPass\u201d 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.<\/span><\/p>\n <\/p>\n
Course Requirements<\/b>\u00a0<\/b><\/h3>\nCore Courses<\/b><\/h4>\n
6 units from the following core courses with at least 1 unit in each area<\/span><\/p>\n <\/p>\n
Bioinformatics<\/b><\/h4>\n\n- 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.<\/span>\n
\n- QBS 146 Foundations of Bioinformatics I<\/span><\/li>\n
- QBS 145 Computational Immunology<\/span><\/li>\n
- QBS 148 Introduction to Statistical Genetics<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
<\/p>\n
Biostatistics<\/b><\/h4>\n\n- 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).<\/span>\n
\n- QBS 108 Machine Learning<\/span><\/li>\n
- QBS 119 Foundations of Biostatistics I: Applied Biostatistics<\/span><\/li>\n
- QBS 120 Foundations of Biostatistics I: Statistical Theory for the Quantitative Biomedical Sciences\u00a0<\/span><\/li>\n
- QBS 121 Foundations of Biostatistics II: Regression Modeling<\/span><\/li>\n
- QBS 122 Foundations of Biostatistics III: Modeling Complex Data<\/span><\/li>\n
- QBS 124 Advanced Biomedical Data Analysis<\/span><\/li>\n
- QBS 126 Analysis of Densely Collected Longitudinal Data<\/span><\/li>\n
- QBS 177 Methods of Statistical Learning for Big Data<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
<\/p>\n
Epidemiology<\/b><\/h4>\n\n- 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.<\/span>\n
\n- QBS 130 Foundations of Epidemiology I: Theory and Methods<\/span><\/li>\n
- QBS 131 Foundations of Epidemiology II: Theory and Methods\u00a0<\/span><\/li>\n
- QBS 132 Molecular Biologic Markers in Human Health Studies<\/span><\/li>\n
- QBS 133 Clinical Epidemiology<\/span><\/li>\n
- QBS 136 Applied Epidemiological Methods<\/span> (0.5 unit)<\/span><\/li>\n
- QBS 137 Applied Epidemiological Methods II<\/span> (0.5 unit)<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
<\/p>\n
Electives Courses<\/b><\/h4>\n
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)<\/span><\/p>\n\n- QBS 101 Foundations of Programming for Data Scientists<\/span><\/li>\n
- QBS 101.1 Intermediate Programming (winter)<\/span><\/li>\n
- QBS 103 Foundations of Data Science<\/span><\/li>\n
- QBS 108 Applied Machine Learning<\/span><\/li>\n
- QBS 119 Foundations of Biostatistics I: Applied Biostatistics<\/span><\/li>\n
- QBS 120 Foundations of Biostatistics I: Statistical Theory for the Quantitative Biomedical Sciences<\/span><\/li>\n
- QBS 121 Foundations of Biostatistics II: Regression Modeling<\/span><\/li>\n
- QBS 122 Biostatistics III: Modeling Complex Data<\/span><\/li>\n
- QBS 123 Biostatistics Consulting Lab<\/span> (0.5 unit)<\/span><\/li>\n
- QBS 124 Advanced Biomedical Data Analysis<\/span><\/li>\n
- QBS 126 Analysis of Densely Collected Longitudinal Data<\/span><\/li>\n
- QBS 130 Foundations of Epidemiology I: Theory and Methods<\/span><\/li>\n
- QBS 131 Foundations of Epidemiology II: Theory and Methods<\/span><\/li>\n
- QBS 132 Molecular Biologic Markers in Human Health Studies<\/span><\/li>\n
- QBS 133 Clinical Epidemiology<\/span><\/li>\n
- QBS 136 Applied Epidemiological Methods I<\/span> (0.5 unit)<\/span><\/li>\n
- QBS 137 Applied Epidemiological Methods II<\/span> (0.5 unit)<\/span><\/li>\n
- QBS 139 Advanced Methods in Health Services Research<\/span><\/li>\n
- QBS 140 Decision & Cost-Effective Analysis<\/span><\/li>\n
- QBS 145 Computational Immunology<\/span><\/li>\n
- QBS 146 Foundations of Bioinformatics I<\/span><\/li>\n
- QBS 147 Genomics: From Data to Analysis<\/span><\/li>\n
- QBS 148 Introduction to Statistical Genetics<\/span><\/li>\n
- QBS 177 Methods of Statistical Learning for Big Data<\/span><\/li>\n
- QBS 180 Data Visualization<\/span> (0.5 unit)<\/span><\/li>\n
- QBS 181 Data Wrangling<\/span><\/li>\n
- QBS 192 Health Informatics<\/span><\/li>\n
- QBS 195 Independent Study<\/span><\/li>\n<\/ul>\n
<\/p>\n