Quantitative Biosciences and Engineering
Doctor of Philosophy
Delivery Options
Fall 2026 Deadline
Priority: December 15th
Domestic: July 1st
International: March 1st
Department
Why study this degree at Mines?
Modern biology is increasingly quantitative. Advances in measurement, computation and modeling are changing how biological systems are studied, designed and engineered. From cellular processes to complex biological networks, the ability to combine biological insight with engineering and analytical tools is now essential. Organizations need experts who can move beyond descriptive biology and develop predictive, testable frameworks grounded in data.
A PhD in Quantitative Biosciences and Engineering from Colorado School of Mines prepares you to work at that intersection. This interdisciplinary program is built for you if you want to apply quantitative thinking to biological questions that matter in research, medicine and industry. Mines is known for applied science and engineering, and that mindset shapes this PhD. Your research will emphasize rigor, reproducibility and clear links between data, models and biological behavior. You will develop the depth needed to advance bioscience while maintaining a strong engineering perspective.
Program Overview
The Quantitative Biosciences and Engineering PhD is an on-campus, interdisciplinary doctoral program drawing on faculty and resources across Mines. It is designed for you if you want to pursue original research that blends biology with engineering, mathematics and computation.
This program will show you how to strengthen your foundation in biological systems and analytical thinking while gaining advanced training in modeling, data analysis and experimental design. Coursework is flexible and selected to directly support your dissertation research.
What you’ll study and do
Your coursework is tailored to your research focus and may span biosciences, chemical engineering, mechanical engineering, applied mathematics and computer science. Topics may include systems biology, biomolecular engineering, computational modeling, data analysis and quantitative experimentation. Coursework is chosen to reinforce your research rather than compete with it.
The center of the program is independent research. You will define a quantitative biological problem, design a rigorous approach to address it and generate results that make an original contribution to the field. Research methods may include laboratory experimentation, computational modeling, data-driven analysis or integrated experimental–computational approaches. You will work closely with a faculty advisor and interdisciplinary committee and complete proposal, candidacy and dissertation defense milestones.
What it takes to complete the PhD at Mines
Completion of the PhD requires advanced coursework, successful completion of qualifying and candidacy requirements and a defended dissertation. As an on-campus program, the experience emphasizes immersion in research groups, collaboration across disciplines and participation in seminars. Mines’ applied environment ensures your work stays connected to measurable biological behavior and real system constraints.
You and Mines PhD: A Right Fit?
You may be a strong fit for this program if you:
- Enjoy combining biology with quantitative analysis or engineering tools
- Are motivated by data, models and experimental validation
- Have strong preparation in biology, engineering, mathematics or a closely related field
Key Program Research Groups
Quantitative Biosciences and Engineering research at Mines spans biological systems studied through analytical and engineering lenses.
Systems biology and biological networks
This area focuses on understanding interactions within biological systems. Research emphasizes modeling and data integration to explain system behavior. Coursework supports quantitative biology and modeling methods. Careers include research, computational biology and applied bioscience roles.
Biomolecular and cellular engineering
Research examines how biological components function and can be engineered. Methods may include laboratory experimentation paired with quantitative analysis. Graduates pursue roles in research, biotechnology and applied biosciences.
Computational and data-driven biosciences
This field emphasizes extracting insight from biological data using computational tools. Research blends modeling, statistics and biological interpretation. Careers include data-focused research and analytics roles in bioscience.
Quantitative bioengineering and modeling
Research focuses on developing predictive models of biological processes. Methods integrate mathematics, computation and experimentation. This expertise supports careers in research and engineering-driven bioscience.
Interdisciplinary biological systems research
Many projects integrate biosciences with engineering and applied science. This area emphasizes collaboration and translating quantitative insight into usable results.
World Class Labs, Centers and Facilities
The Functional Biomechanics Laboratory improves mobility in impaired and at-risk populations through targeted rehabilitation programs and device interventions. Led by Professor Anne Silverman, the lab investigates whole-body biomechanics with experimental and computational approaches, using motion capture, ground reaction force measurement and electromyography to quantify walking mechanics, coupled with detailed musculoskeletal models to generate movement simulations
Professor Cecilia Diniz Behn applies multiscale mathematical modeling to investigate key research questions in metabolism, sleep and circadian rhythms. Her research group models key dynamics in whole-body metabolism including changes in glucose, glycerol, and insulin; sleep and circadian neurophysiology; and the diverse interactions among these systems.
Associate Professor Melissa Krebs develops biopolymer systems that allow the study of cells’ interactions with their microenvironment and that can be used for both tissue regeneration and therapeutics, with the end goal of improving patient therapies that are available in the clinic.
Faculty Expertise
Application Requirements
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Bachelor's degree
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GRE: Not Required
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Resume or Curriculum Vitae (CV)
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Letters of Recommendations (3 letters).
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Statement of Purpose
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Transcripts
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International students please review the English proficiency requirements
Program Curriculum
View Academic CatalogSalary Outlook
Meidan salary for recent program graduates $66,200. Learn more about Mines' comprehensive career development resources and this degree's salary potential.
Employers who seek Mines graduates include
Biotechnology and life sciences
Companies such as
- Genentech
- Amgen
- Pfizer
- Merck
- Thermo Fisher Scientific
Engineering and technology
Companies such as
- Siemens
- Abbott
- Medtronic
- GE Healthcare
- Roche
Data and analytics
Companies such as
- IBM
- Amazon
- SAS
- Palantir
Research and laboratories
Organizations such as
- National Institutes of Health
- National Laboratory of the Rockies
- Los Alamos National Laboratory
- Sandia National Laboratories
- Broad Institute
Consulting and applied research
Companies such as
- RTI International
- Abt Associates
- Booz Allen Hamilton
- Deloitte
- Accenture
Frequently Asked Questions
Why pursue a PhD in Quantitative Biosciences and Engineering?
A PhD prepares you to create new quantitative approaches for studying biological systems. You learn how to integrate data, models and experiments to generate defensible insight.
How interdisciplinary is this program?
The program is explicitly interdisciplinary. Coursework, advising and research often span biology, engineering and quantitative fields.
What career paths are available after graduation?
Graduates pursue careers in research and development, biotechnology, data-driven bioscience roles and academia.
Do you need a master’s degree to apply?
A master’s degree is helpful but not required. Strong preparation in a relevant technical or biological field is essential.
How does Mines’ applied focus shape this PhD?
Mines emphasizes research that connects theory, data and real systems. Quantitative bioscience research here is expected to be rigorous, reproducible and relevant beyond academic study alone.
Meet Hannah Miller, MS '24
As a senior data analyst at Eli Lilly and Company, Hannah Miller is passionate about leveraging data science to accelerate therapeutic research. Her time at Mines taught her how to approach complex problems from new perspectives and she felt deeply supported along the way. "It is such a special program, every single professor really wants you to succeed and I think that's really rare across engineering programs — you're not just a number to them, you're a person and they want you to do well and they care about you.