Mathematical Biology, BS

4 Years On Campus Bachelors Program

University of Pittsburgh

Program Overview

The BS in Mathematical Biology at the University of Pittsburgh combines mathematics, computation, and biological science to help students understand complex biological systems through quantitative models, analysis, and simulation. It is well suited to students interested in biotechnology, medicine, neuroscience, public health, and scientific research, with training designed to support undergraduate research and the application of quantitative methods to real biological problems.

Curriculum Structure

Year 1: Students establish their foundation in mathematics and biological science through MATH 0220 – Analytic Geometry and Calculus 1, MATH 0230 – Analytic Geometry and Calculus 2, and BIOSC 0150 – Foundations of Biology 1, alongside chemistry and general education courses. The second semester continues with MATH 0230, BIOSC 0160 – Foundations of Biology 2, and CHEM 0120 – General Chemistry 2, building the core scientific knowledge needed for later mathematical modeling.

Year 2: Students progress into more theoretical and applied mathematics while expanding their biological understanding through courses such as MATH 0240 – Analytic Geometry and Calculus 3, MATH 0413 – Introduction to Theoretical Mathematics, and BIOSC 0350 – Genetics. They also begin specialized quantitative study with MATH 1370 – Introduction to Computational Neuroscience, MATH 1180 – Linear Algebra 1, and physics, connecting mathematical techniques with biological and neurological systems.

Year 3: The curriculum becomes increasingly computational and specialized through MATH 1270 – Ordinary Differential Equations 1, MATH 1070 – Numerical Mathematical Analysis, and MATH 1080 – Numerical Math: Linear Algebra. Students then take MATH 1380 – Math Biology, which introduces mathematical methods including differential equations, discrete dynamical systems, stochastic dynamics, cellular automata, and computational approaches for developing and analyzing biological models.

Year 4: Students deepen their applied mathematical expertise through courses such as MATH 1470 – Partial Differential Equations 1, MATH 1530 – Advanced Calculus 1, MATH 1540 – Advanced Calculus 2, and MATH 1560 – Complex Variables & Applications. Biology coursework and electives allow students to connect these advanced methods with areas such as computational biology, neuroscience, evolution, immunology, or other biological fields.

Focus areas: Mathematical modeling, computational biology, computational neuroscience, biological systems, numerical analysis, differential equations, simulation, biotechnology, medicine, public health, biology and neuroscience

Learning outcomes: Mathematical analysis, simulation, quantitative modeling, computational problem-solving, biological interpretation, data-driven analysis, independent research, interdisciplinary scientific reasoning

Professional alignment (accreditation): The University of Pittsburgh is accredited by the Middle States Commission on Higher Education (MSCHE), with accreditation reaffirmed in June 2022. Pitt's official accreditation information does not identify a separate specialized professional accreditation for the BS in Mathematical Biology.

Reputation (employability rankings): The University of Pittsburgh's official Mathematical Biology information highlights its excellence in biomedical research and identifies biotechnology, medicine, and other quantitative fields as career applications, but Pitt does not state a program-specific QS, Guardian, or other employability ranking for the BS in Mathematical Biology.

Experiential Learning (Research, Projects, Internships etc.)

The Mathematical Biology, BS at the University of Pittsburgh gives students hands-on experience applying mathematical analysis, computation, simulation, and modeling to biological systems. Students can develop practical quantitative skills through specialized coursework in computational neuroscience and mathematical biology, while Pitt’s Department of Mathematics provides opportunities for faculty-mentored undergraduate research in areas including disease dynamics, neuroscience, ecology, molecular biology, and immunology.

Students can move from classroom theory into research and computational problem-solving through these Pitt-specific opportunities:

Computational modeling: MATH 1370 – Introduction to Computational Neuroscience and MATH 1380 – Mathematical Biology introduce techniques for independent research and mathematical modeling of biological systems.
Numerical methods: Required courses MATH 1070 – Numerical Mathematical Analysis and MATH 1080 – Numerical Linear Algebra develop quantitative and computational approaches relevant to biological modeling.
Faculty-mentored research: Pitt offers undergraduate students opportunities to conduct mentored research with mathematics faculty, including projects in mathematical biology and computational neuroscience. Recent projects have included modeling SARS-CoV-2 effects on the respiratory tract and research into biological pattern formation.
Mathematical Biology research group: Students can connect with research involving neuroscience, ecology, disease dynamics, molecular and cellular biology, and immunology, using mathematical modeling, simulations, network science, statistical learning, and data-driven discovery.
Mathematics Research Center: The Mathematics Research Center (MRC) supports research activities in mathematical biology, numerical analysis, scientific computing, and other areas through research seminars, workshops, mini-conferences, lecture series, and a visitor program.
Computer facilities and software: The Department of Mathematics provides access to computer labs equipped with workstations and current mathematical software, supporting computational work across the mathematics curriculum.
Honors research: Students pursuing departmental honors can complete an honors thesis under the direction of a mathematics faculty member, providing an opportunity for substantial independent research.
Research-to-career preparation: Pitt identifies biotechnology, medicine, science, engineering, statistics, and related quantitative fields as career areas supported by mathematics programs, while the Mathematical Biology degree specifically prepares students to use quantitative methods in biotechnology, medical, and other fields.
Academic research support: The Dietrich School provides an Office of Undergraduate Research, Scholarship, and Creative Activity, while Mathematical Biology students also have access to the Academic Advising Center and Study Lab.

Progression & Future Opportunities

The BS in Mathematical Biology at the University of Pittsburgh prepares graduates to apply mathematical analysis, simulation, and modeling to biological systems, neuroscience, biotechnology, medicine, and public health. Its quantitative focus can support careers in biotechnology, scientific research, data-driven biology, and related medical fields, while also providing a strong foundation for graduate or professional study.

Typical job roles: Mathematical Biology Researcher, Computational Biology Analyst, Biotechnology Research Associate, Quantitative Life Sciences Analyst.

Career support and employment preparation:

Career services: Pitt Career Center provides one-on-one career consulting, resume and cover-letter support, interview preparation, internship and job searching, career fairs, networking events, and Handshake, Pitt’s career-management platform.
Networking: Pitt Commons connects students with alumni, faculty, staff, and other members of the Pitt community for networking and mentoring, while Handshake provides access to jobs, internships, career fairs, and employer connections.
Research preparation: Students take MATH 1370 – Introduction to Computational Neuroscience and MATH 1380 – Mathematical Biology, which introduce techniques for independent research; students are encouraged to pursue mathematical-biology research opportunities locally and nationally.
Employment pathways: Pitt specifically identifies biotechnology, medicine, science, engineering, finance, statistics, and economics among career areas associated with its mathematics programs.
Employment statistics and salary: Not stated specifically for Mathematical Biology graduates on the official Pitt program sources, so a program-specific employment rate or salary figure is not provided.
University–industry partnerships: Pitt has a major life-sciences commercialization ecosystem involving UPMC, its primary clinical partner, and industry partners. Pitt and UPMC work together to translate biomedical discoveries into clinical and commercial applications, while Pitt BioForge and ElevateBio provide a biomanufacturing environment focused on cell and gene therapies.
Industry research opportunities: Pitt reported $58.1 million in industry-sponsored research expenditures in fiscal year 2025, alongside partnerships spanning health care, biotechnology, AI, and data science.
Long-term accreditation: The University of Pittsburgh is accredited by the Middle States Commission on Higher Education (MSCHE), with accreditation reaffirmed in June 2022 following its decennial review. This institutional accreditation provides continuing academic recognition for the university and its degrees.
Graduation outcomes: The degree develops mathematical analysis, simulation, mathematical modeling, biological knowledge, and quantitative research skills, preparing graduates for quantitative work in biotechnology and medical fields as well as further education.

Further Academic Progression: Graduates can continue into advanced study in mathematics, computational biology, biomedical informatics, or related life-science fields. At Pitt, relevant pathways include the MS or PhD in Mathematics, the Computational Biomedicine & Biotechnology MS, the MS in Biomedical Informatics, and the joint Carnegie Mellon–University of Pittsburgh PhD in Computational Biology, which provides interdisciplinary training at the intersection of biology, mathematics, computer science, engineering, and medicine.