BS/MS HDS
The George Washington University Milken Institute School of Public Health (SPH) offers a unique opportunity to students interested in public health and biomedical research. To further effectively train a workforce in public health and related fields with strong data science and data analytics skills, we have developed a dual degree program for students to earn both a BS and MS degree. This dual degree program is designed for undergraduates in a BS program at GWU (e.g., public health, biology, neuroscience, computer science, statistics, mathematics, bioengineering, etc.) different than the BS HDS program (for those see our BS HDS/MS HDS dual degree program) or students who have already completed some undergraduate coursework on health data science at other universities, with an interest in adding health data science expertise to their existing skillsets. This program would result in the earning of a BS degree and a MS degree in Health Data Science (BS/MS HDS program). The program is designed for George Washington University residential and non-residential undergraduates.
Students enrolled in any BS program at GWU (except BS HDS) or students who have already completed some undergraduate coursework on other Health Data Science programs at other universities can benefit from this opportunity to acquire a dual degree by joining the BS/MS HDS program, Bioinformatics concentration. This dual degree program strives to matriculate leaders in public health and biomedical researchers who are committed to life-long learning and to improving the health and well-being of our local, national, and international communities. This is an appropriate program for pre-professional students who are interested in public health issues and translational research.
Program Director: Dr. Ali Rahnavard and Dr. Marcos Pérez Losada
Join T.E.A.M Milken! T.E.A.M. Milken is open to all GWSPH undergraduate majors. Our goal is to provide individualized support to students so you will thrive at GW and be prepared to launch your public health career.
Per GW policy, undergraduate students may not take courses on-line during the fall or spring semesters.
Credit Distribution
Undergraduate courses for the BS |
Follow requirements in the student’s corresponding BS program |
Graduate courses for the MS HDS – Bioinformatics Concentration (36 total credits including 9 crossover credits*) | ||
---|---|---|
PUBH 6850 | 1 | Introduction to SAS for Public Health Research |
PUBH 6851 | 1 | Introduction to R for Public Health Research |
PUBH 6852 | 1 | Introduction to Python for Public Health Research |
PUBH 6080 | 0 | Pathways to Public Health |
PUBH 6860 | 3 | Principles of Bioinformatics |
PUBH 6854 | 3 | Applied Computing in Health Data Science |
PUBH 6859 | 3 | High Performance and Cloud Computing |
PUBH 6861 | 3 | Public Health Genomics |
PUBH 6884 | 3 | Bioinformatics Algorithms and Data Structures |
PUBH 8870 | 3 | Statistical Inference for Public Health Research I |
PUBH 8885 | 3 | Computational Biology |
PUBH 6886 | 3 | Statistical and Machine Learning for Public Health Research |
PUBH 68xx | 6 | Electives |
PUBH 6897 | 2 | Research in Biostatistics and Bioinformatics |
PUBH 6898 | 1 | Master of Science Thesis |
Total graduate credits | 36 credits |
*Students can take up to 9 credits of the MS courses listed below instead of the corresponding course in
their BS program if approved by the HDS graduate advisor
- Pre-Medical Professional
The Bachelor of Science (BS) in Health Data Science with Pre-Medical Professional Concentration program offers students the chance to acquire knowledge and skills in data science, statistics, machine learning and public health.
Concentration Requirements
BISC 1112 | Biology II (4 credits)
CHEM 1111 | General Chemistry I (4 credits)
CHEM 1112 | General Chemistry II (4 credits)
CHEM 2151/2153 | Organic Chemistry I (4 credits)
CHEM 2152/2154 | Organic Chemistry II (4 credits)
BISC 3261 or CHEM 3165 | Introduction to Biochemistry (3 credit)
PHYS 1011 or 1021 or 1025 | General Physics I (4 credits)
PHYS 1012 or 1022 or 1026 | General Physics II (4 credits)PSYC 1001 or SOC 1001 | Psychology or Sociology (3 credits)
CONCENTRATION TOTAL: 34 credits
124 Credits | TOTAL- Pre-Medical Professional Concentration
Guided Electives: the courses provided on the Guided Electives list have been identified as highly relevant to the BS in Health Data Science curricula. A minimum of 9 credits are required to be selected from this approved list of 'guided elective' courses for the Pre-medical Professional concentration.
General Electives: 18 additional credits can also be chosen from the Guided Elective list, or any other undergraduate course at the University, except LSPA designated courses.
For the most up to date list of program courses and program requirements and approved guided electives, please reference the program guide.
The online application will be made available here for three weeks prior to the admissions deadline in the late spring. The application requires the following:
- The online application is available HERE until July 1st and requires the following:
A personal statement. - Your resume.
- Your unofficial transcript from BanWeb.
- GREs are not required, but scores will be accepted.
Admission to the program is made on a selective and space-available basis. Each department's admissions committee considers applications holistically, evaluating applicants' academic strengths, commitment to public health, leadership qualities, and other attributes.
All applicants to the dual BS/MS HDS - Bioinformatics concentration program must have completed the following prerequisites with a grade of B or better to be considered for admission:
- a course in undergraduate statistics
- a course in undergraduate biology
- a course in undergraduate computer science
Dr. Ali Rahnavard, Program Director
Dr. Qing Pan
Dr. Pramita Bagchi
HERE is the complete list of DBB faculty
Students should continue to work with their current undergraduate advisor.
For more information about the program and graduate advising questions, please contact Ali Rahnavard, [email protected].