Modern biomedical research increasingly depends on both multidisciplinary and interdisciplinary approaches. While multidisciplinary work draws from distinct scientific disciplines to address research questions, interdisciplinary research integrates methods and concepts across these disciplines to tackle complex biomedical challenges in innovative ways.
A data explosion resulting from advances in technologies such as next-generation sequencing, mass spectrometry, single-cell genomics, and electronic health records has generated a significant demand for researchers trained in quantitative disciplines such as bioinformatics, biostatistics and epidemiology. Those best positioned to lead this work are cross-trained in multiple quantitative disciplines allowing them to take a truly interdisciplinary approach to solving complex biomedical problems.
Through rigorous training and interdisciplinary collaboration, the QBS doctoral program prepares students for impactful careers at the intersection of biomedical research and quantitative science.
The overall Learning Outcomes for the degree are as follows:
1. Demonstrate comprehensive and foundational knowledge of the core concepts and principles within the field of study
2. Critically analyze and interpret relevant, scholarly literature relevant to the field
3. Integrate and synthesize theoretical and empirical ideas across the field of study
4. Apply the research methods, analytical tools, and techniques essential to scholarly inquiry in the field
5. Assess and critique empirical data and research findings using appropriate methodological frameworks
6. Develop and effectively communicate a research proposal through clear, well-structured written and oral presentations
The requirements for the PhD degree in Quantitative Biomedical Sciences are listed below.
Required Coursework
Ethics
QBS 110
- QBS 110 Integrative Biomedical Sciences Seminar & Programming Workshop (0.5 unit)
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 145 Computational Immuniology
- QBS 146 Foundations of Bioinformatics I
- QBS 148 Introduction to Statistical Genetics
Biostatistics
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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
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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 Modern Clinical Epidemiology: Causal Inference
- QBS 136 Applied Epidemiological Methods (0.5 unit)
- QBS 137 Applied Epidemiological Methods II (0.5 unit)
Electives
Choose 3.5 units from this list
QBS:
- 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
- QBS 137 Applied Epidemiological Methods II (0.5 unit)
- QBS 138 Clinical Trials Design
- 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 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
Thayer School of Engineering:
- ENGM 179.1 Strategy (0.5 unit)
- ENGM 181 Marketing
- ENGM 182 Data Analytics
- ENGM 183 Operations Management
- ENGM 184 Introduction to Optimization Methods
- ENGM 188 Law for Technology and Entrepreneurship
- ENGM 189.1 Medical Device Commercialization (0.5 unit)
- ENGM 189.2 Medical Device Development (0.5 unit)
- ENGM 190 Platform Design, Management, and Strategy
- ENGM 191 Product Design and Development
- ENGM 204 Data Analytics Project Lab
- ENGS 102 Game-theoretic Design, Learning and Engineering
- ENGS 162 Basic Biological Circuit Engineering
- ENGS 262 Advanced Biological Circuit Engineering
Computer Science:
- COSC 169 Topics in Computer Systems
- COSC 174/74 Machine Learning and Statistical Data Analysis
- COSC 178/78 Deep Learning
- COSC 189 Topics in Applied Computer Science
- COSC 258 Operating Systems
- COSC 267 Introduction to Human Computer Interaction
- COSC 274 Machine Learning and Statistical Data Analysis
- COSC 276 Artificial Intelligence
- COSC 278 Deep Learning
- COSC 281 Principles of Robot Design and Programming
Public Health:
- PH 114 Contemporary Issues in Biotechnology: The Practitioner's Perspective (0.5 unit)
- PH 115 Value and Resource Allocation
- PH 122 Survey Methods
- PH 125 Qualitative Methods (0.5 unit)
- PH 128: Health Systems (0.5 unit)
- PH 130 Practical Approaches for Today's Health Care Ethics Challenges (Elective Short Course)
- PH 131 Patient Centered Health Communication (0.5 unit)
- PH 140 Applying Health Statistics (1.5 units)
- PH 147/QBS 139 Advanced Health Services Research with ILE Project (0.5 unit)
- PH 151 Environmental Health Sciences and Policy (0.5 unit)
- PH 154 Drivers of Health Inequities (0.5 unit)
Additional A & S Courses:
- BIOL 147 Genomics: From Data to Analysis
- BIOL 176 Advanced Genetics
- GENE 145 Genomics of Human Disease
- MATH 100 Topics in Probability Theory
- MATH 106 Stochastic Processes with Applications
- PSYC 174 Computational Neuroscience: Brain Engineering
- Communicating Science
Journal Club Requirements
- Completion of the QBS 270 QBS First-Year Journal Club in the each term of year one (0.5 unit)
- Completion of 3 additional approved journal club courses
QBS Journal Club Offerings
- QBS 193 Independent Journal Club (0.5 unit)
- QBS 194 Biostatistics Journal Club (0.5 unit)
- QBS 271 Advanced Epidemiology Journal Club (0.5 unit)
Additional Journal Club Offerings
- BIOL 265 Microbial Ecology and Environmental Biology
- BIOL 268 Genes and Gene Products
- COSC 189 Topics in Applied Computer Science
- ENGG 260 Advances in Biotechnology
- GENE 261 Cancer Biology
- MICR 264 and 265 Microbiology and Immunology - Graduate Research Colloquium
Limits and Requirements
- QBS 195 Independent Study (1 unit) and QBS 123 Biostatistics Consulting (0.5 unit) may be taken multiple times, but only 2 units total in these courses will count toward elective credit.
- Seek administrative approval for non-listed electives. Email Dr. Kristine Giffin for additional information.
- Students wishing to take more than 4 units of coursework per quarter are required to discuss their course selection with the QBS Director of Academic & Student Affairs. For the fall quarter, this unit limit does not count QBS 700: Responsible and Ethical Conduct of Research and QBS 110: Integrative Biomedical Sciences Seminar & Programming Workshop.
Research Rotations
- Three first-year research rotations that will consist of three small research projects, conducted with different faculty members for periods of about three months each, and registered research until the completion of the PhD. Students will enroll QBS 197-199 prior to completing their qualifying exam and QBS 297-299 after successful completion of their qualifying exam.
- QBS 197 Graduate Research in Quantitative Biomedical Sciences I (1 unit)
- QBS 198 Graduate Research in Quantitative Biomedical Sciences II (2 units)
- QBS 199 Graduate Research in Quantitative Biomedical Sciences III (3 units)
- QBS 297 Advanced Graduate Research in Quantitative Biomedical Sciences I (1 unit)
- QBS 298 Advanced Graduate Research in Quantitative Biomedical Sciences II (2 units)
- QBS 299 Advanced Graduate Research in Quantitative Biomedical Sciences III (3 units)
Teaching
- One quarter of supervised teaching in a QBS course, unless otherwise approved
The Qualifying Exam and Dissertation Defense
- Satisfactory completion of an oral qualifying examination
- Satisfactory completion of a significant research project and preparation of a thesis describing this research
- Successful defense of the thesis in an oral examination and presentation of the work in a public lecture
For details of program rules and regulations see the QBS Handbook.