At NYU Langone’s Vilcek Institute of Graduate Biomedical Sciences, students in our MS in biomedical informatics program acquire the skills and knowledge needed for careers in biomedical informatics and computational biology. The program is typically 12 months, but students interested in completing it on a part-time basis can submit a request to do so as part of their application.

We provide rigorous hands-on training in designing experiments, generating and analyzing data, and modeling biomedical systems in real-life situations. We also prepare our students to enter the workforce by enhancing their consulting, communication, and teamwork skills.

Our program teaches the core competencies needed for the American Board of Medical Specialties subspecialty certification in clinical informatics and benefits junior faculty and early-career investigators interested in additional training in informatics.

MS in Biomedical Informatics Curriculum

Our MS in biomedical informatics requires a minimum of 34 credits, including core and elective courses, as well as completion of a written thesis, oral defense, and practical work experience. The practicum is a research experience that serves as both practical work experience and your final MS thesis project. All students must complete a research practicum under the mentorship of a faculty member selected by the student.

We are now offering two specialized tracks within our Biomedical Informatics MS Program.

• Genomics and Bioinformatics track
• Healthcare Artificial Intelligence (AI) track

Program Timeline

The program begins in the summer and spans the next two semesters, with an additional consulting practicum the following summer. Details of the curriculum are as follows.

Summer I: Introductory Coursework (6 credits)

• Introduction to Programming
• Advanced Topics in Biomedical Informatics
• Programming for Data Analysis

Fall: Core Coursework (12 credits)

• Bioinformatics
• Introduction to Healthcare AI
• Healthcare Data Management
• Machine Learning
• Quantitative Methods and Biostatistics

Spring: Advanced Coursework (12 credits)

• Electives (two courses)
• Biomedical Informatics Practicum I
• Professional Studies in Biomedical Informatics

Summer II: Research (4 credits)

• Biomedical Informatics Practicum II

Genomics and Bioinformatics Track

Participation in 3 of the following core Fall courses

• Introduction to Healthcare AI
• Healthcare Data Management
• Machine Learning
• Fundamental Algorithms
• Realtime and Big Data Analytics

Participation in 2 of the following advanced Spring courses

• Advanced Integrative Omics (BMIN-GA 4498, 3 credits)
• Applied Sequencing Informatics (BMIN-GA 3004, 3 credits)
• Deep Learning for Biomedical Data (BMSC-GA 4439, 3 credits, requires prerequisite Machine Learning BMIN-GA 1004)
• Introduction to Single-Cell Data Analysis (BMIN-GA 4528, 3 credits)
• Proteomics Informatics (BMIN-GA 3003, 3 credits)

Healthcare AI Track

Participation in 3 of the following core Fall courses

• Healthcare Data Management
• Introduction to Healthcare AI
• Machine Learning
• Realtime and Big Data Analytics
• Quantitative Methods and Biostatistics

Participation in 2 of the following advanced Spring courses

• Artificial Intelligence, Generative AI, and Data Science
• Clinical Decision Support
• Deep Learning in Medicine
• Evaluation Methods for Predictive Risk Models
• Natural Language Processing
• Mathematical Techniques for CS Applications
• Database Systems
• Special Topics in Computer Science

MS in Biomedical Informatics Electives

Master’s students in the biomedical informatics program may take electives offered by NYU Grossman School of Medicine and NYU’s Graduate School of Arts and Science. Examples of electives available to master’s students include the following courses.

Vilcek Institute of Graduate Biomedical Sciences Elective Courses

• Advanced Integrative Omics (BMIN-GA 4498, 3 credits)
• Advanced Regression Modeling (BMSC-GA 4494, 3 credits)
• Applied Sequencing Informatics (BMIN-GA 3004, 3 credits)
• Artificial Intelligence, Generative AI, and Data Science (BMIN-GA 4527, 3 credits)
• Clinical Decision Support (BMIN-GA 3002, 3 credits)
• Consulting in Biomedical Informatics (BMIN-GA 3005, 3 credits)
• Deep Learning for Biomedical Data (BMSC-GA 4439, 3 credits, requires prerequisite Machine Learning BMIN-GA 1004)
• Evaluation Methods for Predictive Risk Models (BMIN-GA 3008, 3 credits)
• Independent Studies in BMI (BMIN-GA 2005, 0-6 credits)
• Introduction to Biomedical Entrepreneurship: Foundations of Biomedical Start-Ups (Fall, BMSC-GA 4525, 1 credit)
• Introduction to Single-Cell Data Analysis (BMIN-GA 4528, 3 credits)
• Proteomics Informatics (BMIN-GA 3003, 3 credits)

NYU Cross-Listed Elective Courses

• Translational Genomics and Computational Biology (Fall, BMIN-GA 7733, 3 credits), Tandon School of Engineering
• Applied Statistics for Bioinformatics (Fall, BMIN-GA 7673, 3 credits), Tandon School of Engineering
• Realtime and Big Data Analytics (Fall, BMIN-GA 2436, 3 credits), Computer Science
• Fundamental Algorithms (Fall, BMIN-GA 1170, 3 credits), Computer Science
• Population Genetics and Evolutionary Biology for Bioinformatics (Fall, BMIN-GA 7693, 3 credits), Tandon School of Engineering
• Special Topics in Computer Science (Fall/Spring, BMIN-GA 3033, 3 credits), Computer Science
• Statistics and Math for Bioinformatics (Spring, BMIN-GA 7723, 3 credits), Tandon School of Engineering
• Bioinformatics I Algorithms in Bioinformatics (Spring, BMIN-GA 7453, 3 credits), Tandon School of Engineering
• Mathematical Techniques for CS applications (Spring, BMIN-GA 1180, 3 credits), Computer Science
• Natural Language Processing (Spring, BMIN-GA 2590, 4 credits), Computer Science
• Database Systems (Spring/Summer, BMIN-GA 2433, 3 credits), Computer Science