Master of Science Computational Biomedicine and Biotechnology

Advance a global revolution in precision diagnostics, drug discovery, and novel therapeutic targets.

Pursue Your Breakthrough Professional Master's at a World-Renowned Medical School.

Pitt’s Master of Science in Computational Biomedicine and Biotechnology gathers undergraduates from biology, mathematics, physics, engineering, chemistry, computer science, or any quantitative background. You will join a community of scientists, clinicians, educators, and entrepreneurs working at the intersection of computing, machine learning, artificial intelligence (AI), and cell-level medicine.

This vanguard is driving global advances in healthcare, transforming our approach to diagnosis, treatment, and personalized care—at the University of Pittsburgh School of Medicine and beyond.

Five Distinct Computational Bio Career Tracks

We meet a growing demand for professionals with knowledge across disciplines and an integrative mindset. The University of Pittsburgh's Computational Biomedicine and Biotechnology Master's program allows you to design a master's degree that fits your precise skills, experience, and career goals.

Data Science, Programming, Probability, and Statistics Master data-driven biomedical research, healthcare analytics, and bioinformatics.

Artificial Intelligence, Machine Learning, and Bioimage Analysis Master medical imaging, diagnostics, and AI-driven research.

Genomics and Precision Medicine Master genetic research, personalized medicine, and clinical genomics.

Molecular & Cellular Systems Modeling Master computational biology, systems biology, and biomedical modeling.

Drug Discovery and Quantitative Pharmacology Master pharmaceutical research, drug design, and therapeutic innovation.

5 Concentrations Tailor a path to a career in research, industry, or innovation.

$130,000-$140,000 Salary range for typical biomedicine/biotech specialists.

12-20 Months Program duration.

Find Your Gateway to Industry Leaders

Take courses in Genomics, Modeling and Drug Design, and Artificial Intelligence that prepare you to work in the pharmaceutical industry (Roche, Merck, or Pfizer). Alternatively, aim for a Medical Imaging and Diagnostics career with companies like GE Healthcare — leveraging specialized training in Artificial Intelligence, Machine Learning, and Bioimage Analysis techniques.

Sharpen Your Core and Interdisciplinary Skills

Excel amidst a broader industry trend toward interdisciplinary team work. Join biomedical and biotechnology teams sharing knowledge across machine learning (ML) and artificial intelligence (AI). Build upon a foundation of programming/coding skills and their application to molecular simulations, computer-based image processing and analysis, big data management, bioinformatics, and genomics.

Clear Pathway to a PhD

Benefit from courses that overlap with three related doctoral programs: the Carnegie Mellon University-University of Pittsburgh joint PhD program in Computational Biology; the Biomedical Informatics PhD program, and the Integrative Systems Biology PhD program. Pursue early application to the CMU-Pitt joint program, or choose elective from any school or department at the University of Pittsburgh.

Network and Grow

Gain hands-on experience and engage real-world problems in computational biology. Select a research mentor and complete at least four credits of Directed Study during your second and/or third semesters. Network and explore summer internships across industrial laboratories, biotech and pharmaceutical companies, and governmental organizations — employers like UPMC Enterprises and Janssen Pharmaceuticals.

Connected Institutes and Centers

U.S. News & World Report Top Tier for Research

World-Renowned: The University of Pittsburgh School of Medicine

Tier-1: Best Medical Schools: Research (U.S. News & World Report)
Top 10: Biomedical Engineering (ARWU, Shanghai Ranking)
Top 10: U.S. Medical Schools in NIH funding ($658.3M)
Top 15: Human Biological Sciences (ARWU, Shanghai Ranking)
Top 15: Medical Technology (ARWU, Shanghai Ranking)

Industry Innovation

Seek a role as a research scientist or engineer in a biotech firm and contribute to product development in areas like synthetic biology or genomics.

Consulting and Strategy

Combine your science and technology background with compliance and commercialization savvy as a biotech consultant or equity research analyst. Advise companies on market trends and investment strategies.

Academic Research and Development

Pursue an R&D position in biotechnology or computational biology and focus on advancing foundational knowledge while training the next generation of scientists.

Entrepreneurship

Join the ranks of a start-up in emerging biotech fields (e.g., genome editing platforms or AI-driven drug discovery) and capitalize on disruptive technologies to address unmet needs.

Faculty Spotlight

Learn from renowned scholars, researchers, and practitioners who offer insider perspectives and real-world insight. As you tackle today's most complex Computational Biomedicine and Biotechnology challenges, these highly accomplished scholars, clinicians, and industry leaders will be your teachers and mentors.

Mert Gur, Ph.D. Associate Professor Dr. Gur’s research focuses on computational modeling and statistical thermodynamics, particularly biomolecular machines and motor/membrane proteins. Potential applications include diagnosing mutations for early cancer detection, developing cell-penetrating peptide-based drugs, and developing novel therapeutic strategies to inhibit or regulate protein functions.

Anne Ruxandra Carvunis, Ph.D. Associate Professor Dr. Carvunis combines computational and experimental methods to explore fundamental questions about the origins of new genes, focusing on microproteins and the immune system from an evolutionary perspective. She received the 2023 NIH Director’s Transformative Research Award for the project "Unraveling Microprotein Biology with an Evolutionary-Immunological Framework."

Shikhar Uttam, Ph.D. Assistant Professor was awarded a Single-Cell Biology Data Insights grant from the Chan Zuckerberg Initiative (CZI) to support his computational biology research. This grant is part of the CZI Cell Science program.

Research Areas of Focus

Biological Systems Modeling

Join investigations within Computational and Systems Biology (CSB) research exploring gene birth on evolutionary time scales, protein structure dynamics, and immune cell interactions.

Systems Genetics

Partner with investigators exploring large-scale experimental and computational approaches to map the connections between genetic changes and traits (including disease) and translate genomes into mechanistic insights and actionable understanding (e.g., precision therapy).Image © Gur Lab

Molecular Mechanism and Therapeutics

Learn how the molecular forces driving the shapes, interactions, and dynamics of proteins and other biological macromolecules enable computational and systems pharmacology approaches to discover therapeutics that modulate macromolecular systems.Image © Gur Lab

Join investigations within Computational and Systems Biology (CSB) research exploring gene birth on evolutionary time scales, protein structure dynamics, and immune cell interactions.

1. Precision Medicine Specialist

Focus: Tailor treatments based on genetic, environmental, and lifestyle factors.

Skills: Genomics, bioinformatics, pharmacology, and genetic counseling.

Applications: Targeted cancer therapies and personalized diabetes management.

2. Bioinformatics Data Scientist

Focus: Analyze biological data to derive actionable insights.

Skills: Programming (Python/R), statistical analysis, machine learning, genomics.

Applications: Biomarker identification, protein structure prediction, and drug development optimization.

3. Synthetic Biology Engineer

Focus: Designing and engineering organisms for specific applications.

Skills: Molecular cloning, CRISPR genome editing, systems biology, lab automation.

Applications: Develop synthetic gene circuits for targeted cancer therapies, infectious disease treatments, and metabolic disorders or live therapeutics for tissue regeneration.

4. Biotech Product Manager

Focus: Bridging science and business to bring innovations to market.

Skills: Leadership, strategy development, technical expertise in biotechnology.

Applications: Integrating artificial intelligence and data analytics into diagnostic and treatment decision support systems.

5. Genomic Data Scientist

Focus: Interpreting genomic variations for health insights.

Skills: Computational genomics tools (e.g., GATK), statistical modeling.

Applications: Disease risk prediction, population genomics studies.

6. AI/ML Specialist in Drug Design

Focus: Applying machine learning to accelerate drug discovery.

Skills: Neural networks (e.g., generative AI), molecular modeling software.

Applications: Predicting drug efficacy and side effects, optimizing molecular structures.

7. Biomedical Systems Analyst

Focus: Integrating multimodal healthcare data for clinical insights.

Skills: Systems biology modeling, data integration tools (e.g., Cytoscape).

Applications: Utilizing machine learning and AI to forecast patient outcomes and optimize resource allocation.

Featured Alumni

Arjun Singh '24 MS Computational Biomedicine and Bio Technology Bioinformatics Research Specialist at UPMC Hillman Cancer Center

Sneha Mittal '23 MS Computational Biomedicine and Bio Technology Bioinformatics Analyst at New York Genome Center

Haotian Zhang '20 MS Computational Biomedicine and Bio Technology Ph.D., CMU-PITT Computational Biology Ph.D. Program

Nishita Kalepalli '23 MS Computational Biomedicine and Bio Technology Data Scientist at Vascular Medicine Institute