Frequently Asked Questions

No. Candidates do not need to take the GRE in order to apply for this program.

All applicants are required to demonstrate a level of proficiency in the English language sufficient to meet the admission requirement of the Graduate School of Arts & Sciences. Follow the TOEFL/IELTS instructions in Admissions FAQ to determine whether you need to send us test scores to prove your English language proficiency.

No. This program meets in person only at Georgetown University.

Yes. Students will have up to three years to complete this program on a part-time basis. Unfortunately, this option is not available for International students on an F-1 visa.

No. The HIDS program only accepts applications for Fall admission.

Prior medical knowledge is not necessary for admission. The medical terminology and operational aspects of health care systems will be taught in two introductory courses that students will take in the Fall semester.

All courses will deal with medical concepts as well as data science concepts. In courses, students will be using programming languages (R or Python) to acquire, process, analyze and visualize medical and/or life sciences datasets. The medical knowledge needed to do the exercises and tests will be taught during the course of the class.

Prospective students must demonstrate programming skills and quantitative skills. Students will learn machine learning, deep learning and statistical methods in our courses, but the focus of the HIDS program is not biostatistics. The focus is on learning how to apply data science approaches to health care data.

Health Informatics and Data Science (HIDS) is a multidisciplinary field concerned with the optimal use of information, often aided by health information technology and tools, to improve individual health, health care, public health and biomedical research. It helps in the collection, organization, standardization of health data in a manner that is readily usable for analysis to improve current care processes and clinical research. HIDS assists in identifying novel insights on the health condition of patients and care processes. It also helps in improving the quality of care by generating better information and knowledge from patients’ data to improve outcomes, safety and costs.
Example courses include: HIDS 6001 Massive Health Data Fundamentals, HIDS 7003 Precision Health Informatics, HIDS 7006 AI for Health Applications, HIDS 7007 Digital Health Applications
Prospective students will have undergraduate or advanced degrees in any field of engineering or life sciences, including computer science, math, physics, engineering, information systems, health informatics, biomedical sciences, medicine, nursing, or related fields.
Graduates from the program will be ready to take on roles such as data scientist, data analyst, programmer, health business analyst, electronic health record (EHR) data manager, health technology consultant, nurse informatician, Chief Medical Informatics Officer (CMIO), Chief Analytics Officer (CAO), and other related positions.

Systems Medicine relies on systems biology and multi-omics approaches and tools in solving biomedical problems.
Example courses include: Biomedical Informatics, Clinical Informatics, Application of Biostatistics to “Big Data”, Clinical Applications of the Microbiota, Application of Biostatistics to “Big Data”, Critical Reading in Systems Medicine, Systems Medicine Internship
Prospective students: will have undergraduate degrees in biology, life sciences, statistics or related fields.
Graduates from the program will be ready to take on roles such as bioinformatics analysts or biocurators, or to pursue advanced degrees (e.g., M.D., Ph.D.).

Bioinformatics is the field that develops methods and software tools for understanding biological data. The goal of bioinformatics is to enable the discovery of new biological insights, as well as to create a global perspective from which unifying principles in biology can be discerned. Bioinformatics helps in sequencing genes and understanding the role of DNA, genes, and chromosomes. Experts in bioinformatics study protein structures using their functions. They also build 3-D models of molecules, cells, tissues, systems, and even entire organisms.
Example courses include: Bioinformatics Computing, Molecular Biology for Bioinformatics, Biostatistics, Machine Learning for Bioinformatics, Next Generation Sequencing Data Analysis, Intro to Experimental Design & Data Analysis
Prospective students will have undergraduate degrees in biology, computer science, mathematics, statistics or related fields.
Graduates from the program will be ready to take on roles such as bioinformatician, molecular biologist, research associate, and other related positions.

Biostatistics is the application of statistics to a wide range of topics in biology. It encompasses the design of experiments especially in life sciences, medicine, pharmacy and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results.
Example courses include: Probability & Sampling, Statistical Inference, Linear Models & Multivariate Analysis
Prospective students will have undergraduate degrees with basic courses in statistics, multivariable calculus, and linear algebra.
Graduates from the program will be ready to take on roles such as biostatistician, clinical trial statistician, data manager, research associate, and other related positions.

Application fee waivers may be available. View information about the application fee and fee waivers.