Ph.D. in Biomedical Data Science and Informatics (Clemson-MUSC Joint Program)

Biomedical data science and informatics is an interdisciplinary field that applies concepts and methods from computer science and other quantitative disciplines together with principles of information science to solve challenging problems in biology, medicine and public health.

The nation's transition to new healthcare delivery models and the exponential growth in biomedical data translate to a need for professionals with expertise in data science focused in biomedical research who can leverage big data to improve health in the state and the nation. Specialized tracks include precision medicine, population health, and clinical and translational informatics.

The program is a unique collaboration that brings together Clemson's strengths in computing, engineering, and public health and MUSC's expertise in biomedical sciences to produce the next generation of data scientists, prepared to manage and analyze big data sources from mobile sensors to genomic and imaging technologies. Graduates will possess the necessary skills for informatics careers in biology, medicine or public health focused on the development of prescriptive analytics from large data sources.

Admissions

Learn more about the admission steps and requirements for the program.

Curriculum

Each student will work with the graduate coordinator, academic advisor, and dissertation committee to construct a program of study that conforms to the requirements outlined below and takes into account both the student’s prior preparation and intended research area. In cases where the student comes to the program with prior coursework in a required area, the graduate coordinator may approve a substitution. In cases where a student lacks pre-requisites for a required course, the student will be asked to complete both the pre-requisite coursework and the required course. Because the curriculum will be tailored to each student, the time needed to complete the degree will vary, but in general, it is expected that students can complete the degree in five years or less.

Coursework (65-68 credit hours):

Area I - Biomedical Informatics Foundations & Applications 15-16 credit hours
Area II - Computing, Math, Statistics, & Engineering 18 credit hours
Area III - Population Health, Health Systems, & Policy 5-6 credit hours
Area IV - Domain Biology/Medicine 3-4 credit hours
Area V - Lab rotations, seminars, doctoral research 24 credit hours

Additional requirements include passing a qualifying exam, a dissertation proposal, and ultimately a dissertation and its defense.

Students will have a designated "home institution" -- either Clemson or MUSC -- at which they will be physically located. However, all students in this program will take graduate classes from both institutions. Students will not be required to travel between campuses as courses will be made available to students both on-campus and via synchronous remote capability. Courses will be offered at the Clemson main campus, MUSC main campus, the University Center at Greenville, and the Zucker Family Graduate Education Center (on CURI campus, North Charleston).

This doctoral program is a research degree. Students will pursue one of three track specialty areas which include precision medicine, population health, and clinical and translational informatics. All students will have the opportunity to work directly with one or more program faculty members on research related to data science and informatics. Doctoral students will be immersed in the research environment and will actively engage in authoring research proposals, conducting research, writing abstracts and manuscripts, and presenting research findings.

*This course is delivered through Clemson University as part of a joint Biomedical Data Science and Informatics program.

Area I - Biomedical Informatics Foundations & Applications

Biomedical Informatics Foundations
BDSI 701
(MUSC)
Introduction to Biomedical Informatics 3
BDSI 702
(MUSC)
Biomedical Data Standards 3
Research Foundations (Choose 1)
BDSI 8210
(MUSC)
Health Research I 3
BDSI ####
(MUSC)
Research Principles & Concepts 3
HIN 708
(MUSC)
Applied Statistical & Research Methods 3
Track Specific Course (Choose 1)
BDSI 711
(MUSC)
Precision Medicine Informatics 3
BDSI 712
(MUSC)
Translational Informatics 3
BDSI 8900
(MUSC)
Population Health Informatics 3
Electives (Choose 1-2, Minimum 3 credit hours)
CPSC 8450
(CLEM)
Bioinformatics Algorithms 3
BMTRY 783
(MUSC)
Statistical Methods for Bioinformatics 3
BDSI ####
(MUSC)
Panomics 3
BDSI ####
(MUSC)
Consumer & Quantified Self 3
BDSI ####
(MUSC)
Health Enterprise Analytics 3
BDSI 731
(MUSC)
Microbiome Informatics 3
Area Total 15-16

Area II - Computing, Math, Statistics, & Engineering

Systems & Database Management (Choose 2)
Applied Software Engineering
BDSI 8710
(CLEM)
Foundations of Software Engineering 3
BDSI ####
(CLEM)
Software Design 3
Computing Environments
BDSI ####
(CLEM)
Computational Science 3
BDSI 6780
(CLEM)
General Purpose Copmutation on GPUs 3
BDSI ####
(CLEM)
High Performance Computing with GPUs 3
BDSI 8200
(CLEM)
Parallel Architectures 3
BDSI ####
(CLEM)
Introduction to Parallel Systems 3
BDSI ####
(CLEM)
Principles of Scientific Computing 3
Data Management Tools & Technology
BDSI 6620
(CLEM)
Database Management 3
BDSI ####
(CLEM)
Database Management System Design 3
BDSI ####
(CLEM)
Introduction to Information Retrieval 3
Human Factors, HCI, & Usability
BDSI ####
(CLEM)
Human & Computer Interaction 3
BDSI 8310
(CLEM)
Fundamentals of Human-Centered Computing 3
BDSI 8000
(CLEM)
Human Factors Engineering 3
Performance & Scalability
BDSI ####
(CLEM)
Systems Modeling 3
Math & Computing Foundations (Choose 1)
BDSI 8010
(MUSC)
Statistical Methods I 3
BDSI 8050
(MUSC)
Data Analysis 3
BMTRY 700
(MUSC)
Introduction to Clinical Biostatistics 3
Machine Learning/Data Science (Choose 1)
BDSI 6420
(CLEM)
Artificial Intelligence 3
BDSI 6300
(MUSC)
Applied Data Science 3
BDSI 721
(MUSC)
Applied Machine Learning 3
BDSI ####
(CLEM)
Machine Learning: Implementation & Evaluation 3
BDSI ####
(CLEM)
Advanced Machine Learning 3
Choose 2
Biostatistics
BDSI ####
(CLEM)
Biostatics 3
BDSI 8310A
(MUSC)
Quantitative Analysis 3
BMTRY 701
(MUSC)
Biostatistical Methods II 3
Data Mining
BDSI 8650
(CLEM)
Data Mining 3
BDSI ####
(CLEM)
Pattern Recognition 3
BDSI ####
(CLEM)
Network Science 3
BDSI ####
(CLEM)
Applied Multivariate Statistical Analysis 3
BMTRY 719
(MUSC)
Bayesian Biostatistics 3
Visualization & Exploratory Data Analysis
BDSI 6030
(CLEM)
Data Visualization 3
BDSI ####
(CLEM)
Scientific Visualization 3
BDSI 8430
(CLEM)
Deep Learning 3
Image & Signal Processing
BDSI ####
(CLEM)
Introduction to Computer Vision 3
BDSI ####
(CLEM)
Introduction to Digital Signal Processing 3
BDSI ####
(CLEM)
Digital Image Processing 3
BDSI ####
(CLEM)
Medical Imaging 3
Decision Analysis/Knowledge Integration/Modeling
BDSI 6410
(CLEM)
Introduction to Stochastic Models 3
BDSI ####
(CLEM)
Knowledge Engineering 3
BDSI ####
(CLEM)
Engineering Optimization & Applications 3
Geospatial Analysis
BDSI ####
(CLEM)
GIS for Public Administrators 3
BDSI ####
(CLEM)
GIS & Mapping for Public Health 3
Algorithms/Data Structures
BDSI ####
(CLEM)
Design & Analysis for Algorithms 3
BDSI 8380
(CLEM)
Advanced Data Structures 3
Natural Language Processing
BDSI 722
(MUSC)
Clinical Natural Language Processing 3
Area Total 18

Area III - Population Health, Health Systems, & Policy

Choose 2 (Course titles must be different)
Ethical, Legal & Social Issues, Privacy, and Security
HAP 735
(MUSC)
Health Law & Risk Management 3
HIN 716
(MUSC)
Ethical, Legal, & Regulatory 3
Health Systems
BDSI 8110
(MUSC)
Health Care Delivery Systems 3
HAP 705
(MUSC)
Health Economics 3
DHA 807
(MUSC)
Managing Healthcare Information 3
Health Policy
HAP 704
(MUSC)
Health Policy 3
BDSI ####
(CLEM)
Health Policy 3
Population Health
BDSI ####
(CLEM)
Population Health & Research 2
BDSI ####
(CLEM)
Epidemiology 3
BMTRY 736
(MUSC)
Foundations of Epidemiology I 3
DHA 850
(MUSC)
Population Health Management 3
BMTRY 747
(MUSC)
Foundations of Epidemiology II 3
Quality & Safety
BDSI ####
(CLEM)
Health System Quality Improvement 2
HAP 632
(MUSC)
Quality Management of Health Care Services 3
Area Total 5-6

Area IV - Domain Biology/Medicine

Choose 1
Biochemistry/Pathology
BDSI ####
(CLEM)
Molecular Biology: Genes to Proteins 3
BDSI ####
(CLEM)
Molecular Basis of Disease 3
Foundations of Biomedical Sciences
BDSI ####
(CLEM)
Biomedical Basis for Engineered Replacement 3
CGS 765
(MUSC)
Proteins: Dynamic Structures & Functions 3
CGS 766
(MUSC)
Genes: Inheritance & Expression 4
CGS 767
(MUSC)
Cells: Organization & Communication 3
Genetics
BDSI 6700
(MUSC)
Human Genetics 3
BDSI ####
(CLEM)
Introduction to Applied Genomics 3
Area Total 3-4

Area V - Lab rotations, seminars, doctoral research

Lab Rotations
CGS 720
(MUSC)
Lab Rotation 4
BDSI 700
(MUSC)
BDSI Seminar 4
BDSI 771
(MUSC)
Health Equity 1
BDSI 780
(MUSC)
BDSI Special Topics 1-3
BDSI 970
(MUSC)
Research 18
Area Total 24
Curriculum Total 65-68