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The Sc.B. in Applied Mathematics-Biology at Brown University brings together biology and applied mathematics, giving students the quantitative and analytical skills needed to understand biological systems, work with biological data, and explore areas such as bioinformatics and computational neuroscience. It is a great choice for students who enjoy both mathematics and the life sciences and want to use mathematical, statistical, and computational methods to solve biological and scientific problems.
Curriculum Structure:
Year 1: Students start by developing a strong foundation in mathematics, chemistry, and biology. Courses such as MATH 0180 Multivariable Calculus, MATH 0520 Linear Algebra, CHEM 0330 Equilibrium, Rate, and Structure, and BIOL 0200 The Foundation of Living Systems prepare students for more advanced quantitative and biological study.
Year 2: Students begin applying mathematical methods directly to biological questions. Courses such as APMA 0355 Applied Ordinary Differential Equations with Theory, APMA 1655 Introduction to Probability and Statistics with Theory, and APMA 1070 Quantitative Models of Biological Systems help students learn how to model biological processes and analyse data using mathematical and statistical approaches.
Year 3: Students develop more specialised knowledge by combining advanced mathematics with biological applications. Courses such as APMA 0365 Applied Partial Differential Equations I with Theory and APMA 1080 Inference in Genomics and Molecular Biology, together with upper-level Biology or Neuroscience courses, allow students to explore areas such as genomics, molecular biology, and computational neuroscience.
Year 4: In the final year, students bring together their mathematical, computational, and biological knowledge through advanced coursework and research-focused study. Options can include BIOL 1555 Methods in Informatics and Data Science for Health, BIOL 1565 Biomedical Informatics, or an approved independent research course, giving students opportunities to apply their skills to real scientific questions.
Focus Areas: Applied Mathematics, Biology, Bioinformatics, Computational Biology, Computational Neuroscience, Genomics, Molecular Biology, Probability and Statistics, Biological Systems Modelling, Statistical Inference, Data Analysis
Learning Outcomes: Apply mathematical and statistical methods to biological problems, model biological systems quantitatively, analyse biological and genomic data, develop computational and programming skills, understand core biological principles, interpret scientific data using probability and statistics, connect advanced mathematics with biological research, conduct independent and collaborative research
Professional Alignment (Accreditation): The Sc.B. in Applied Mathematics-Biology provides an interdisciplinary foundation combining quantitative mathematics with biological science. The skills developed in mathematical modelling, statistics, computation, data analysis, and biology can support careers and further study in areas such as bioinformatics, computational biology, biotechnology, healthcare, data science, and scientific research.
Reputation (Employability Rankings): Brown University is recognised as a leading U.S. university, and its graduates have strong opportunities to move into employment or further study. Brown reports that 88% of undergraduate alumni surveyed 10 years after graduation say Brown prepared them for their current career, reflecting the university's strong focus on preparing students for their professional futures.
The Sc.B. in Applied Mathematics-Biology at Brown gives students opportunities to apply mathematics, statistics, computing, and biological knowledge to real research questions. The program ends with a senior capstone that allows students to take part in creative research collaborations with faculty, while independent study and research opportunities let students explore specialised topics in greater depth. Students can also work with researchers across areas such as biology, biostatistics, computer science, neuroscience, engineering, and the Center for Computational Molecular Biology (CCMB).
Students can build practical research and analytical experience through several Brown programmes and activities:
Senior Capstone Research: Students complete a senior capstone that can involve creative research collaboration with Brown faculty, bringing together their mathematical and biological knowledge to investigate real scientific questions.
Independent Study: Through APMA 1970, students can study specialised topics that are not covered in regular courses, working directly with a sponsoring faculty member who provides guidance and develops the study plan.
Directed Reading Program: Students can take part in semester-long independent mathematics reading projects through a one-to-one mentoring arrangement with graduate students.
Faculty Research: Students can pursue research with Applied Mathematics faculty during the summer and can also explore research opportunities with faculty in biology, biostatistics, computer science, engineering, neuroscience, CCMB, and other related fields.
Group Research Projects: Brown's Summer@ICERM programme places selected undergraduate students into small groups of two to four, where they work on interdisciplinary research projects under the guidance of faculty mentors and teaching assistants.
Research Presentations: Summer@ICERM participants regularly present their findings and take part in mini-courses, guest talks, and professional development activities, giving them experience communicating mathematical and scientific research.
Research Internships: Students can pursue REU opportunities at universities across the United States, as well as Brown's Summer Research Early Identification Program (SR-EIP). SR-EIP provides 8–10 week research experiences under the guidance of faculty or research mentors.
Summer Research Support: Brown's SPRINT awards provide support for students undertaking summer research experiences.
Computational and Quantitative Skills: The programme develops practical skills in mathematical modelling, probability, statistical inference, systems dynamics, and computational analysis, which are increasingly important for interpreting large biological datasets and studying biological phenomena.
Interdisciplinary Research Environment: Students can use their mathematics and computing skills in research settings beyond Applied Mathematics, including biology, biostatistics, computer science, neuroscience, engineering, and computational molecular biology.
The Sc.B. in Applied Mathematics-Biology at Brown University gives students a strong foundation for careers that bring together mathematics, biology, computing, and data analysis. The combination of quantitative skills and biological knowledge can open doors to careers in areas such as data science, bioinformatics, scientific research, consulting, and technology, while also providing a strong foundation for further study.
Typical career options include Data Scientist, Bioinformatics Analyst, Computational Biologist, and Data Analyst. Students can also explore opportunities in scientific research, software development, consulting, actuarial science, finance, and other data-focused fields.
Brown provides several resources and opportunities to help students turn their academic experience into meaningful career and further-study opportunities:
Career support: Brown's Lizzie and Jonathan Tisch Center for Career Exploration provides career guidance and connects students with opportunities through Brown's extensive alumni network. Students can also use career exploration resources to understand potential career paths across different industries and fields.
Strong graduate outcomes: Brown reports that 88% of undergraduate alumni surveyed 10 years after graduation say Brown prepared them for their current career. The university also reports that 25% of the Class of 2022 pursued graduate or professional studies, demonstrating that Brown graduates continue into both employment and advanced education.
Research experience: Students can gain valuable experience by working with faculty in Applied Mathematics and related areas such as Biology, Biostatistics, Computer Science, Engineering, Neuroscience, and Computational Biology. Opportunities such as REUs, SR-EIP, Summer@ICERM, SPRINT, and independent research can help students develop experience that is useful for both employment and postgraduate applications.
Industry-relevant skills: Students graduate with experience in scientific computing, probability, statistics, mathematical modelling, data analysis, and quantitative problem-solving. These skills can be applied across technology, healthcare, biotechnology, finance, research, and other data-driven industries.
Interdisciplinary opportunities: Brown's Applied Mathematics community works across fields including computational biology, engineering, computer science, neuroscience, biology, and public health. This interdisciplinary environment allows students to see how mathematical and computational methods are used to solve practical problems in different sectors.
Research strength: Brown's Applied Mathematics Division has substantial externally funded research activity, with research spanning areas such as computational biology, mathematical biology, neuroscience, statistics, scientific computing, and applied probability. Students can benefit from being part of this research-focused academic environment.
Accreditation and degree value: The Applied Mathematics-Biology program is an interdisciplinary Sc.B. rather than an engineering degree, so it should not be presented as an ABET-accredited program. Its value comes from combining STEM-focused mathematical training with biology, computation, statistics, and research experience. Brown identifies the program as STEM eligible.
Preparation for professional careers: Independent research, senior projects, internships, research presentations, and faculty-guided study allow students to build practical experience alongside their academic knowledge. This can give graduates a stronger profile when applying for jobs or competitive postgraduate programmes.
Further Academic Progression: After completing the Sc.B., students can continue into master's or doctoral study depending on their career goals. Possible pathways include applied mathematics, mathematics, computational biology, bioinformatics, biological sciences, neuroscience, statistics, data science, economics, operations research, medicine, and related research areas. Students interested in research careers can use the research experience gained at Brown as a foundation for Ph.D. study and other advanced professional programmes.
Applicants must have a high school diploma or equivalent and submit an official high school transcript, School Report, and Brown’s required supplemental application materials.
Applicants must provide a counselor recommendation and two teacher recommendations; for students applying for a Bachelor of Science degree, Brown recommends that at least one teacher recommendation come from a math or science teacher. US universities use a holistic admissions review. Beyond grades and standardized test scores, they weigh the strength of your overall profile to understand who you are as a student and a person.
Profile Assessment: Science applicants are generally assessed on the rigour of their Mathematics and laboratory-science coursework. Relevant preparation may include Biology, Chemistry, Physics, Calculus or Statistics, depending on the intended field. Research, science fairs, Olympiads, laboratory exposure, independent investigation and environmental or community-science projects can demonstrate scientific curiosity and analytical thinking.Advanced Placement(AP) Guidance: AP availability depends on the student's school. Relevant APs can strengthen an application and may earn university credit, but are not compulsory unless the university or programme explicitly requires them.Extracurricular activities: Estimated contribution: 20–30%. Brown values intellectual curiosity, independence, creativity and community engagement. Activities can demonstrate how the student might use the Open Curriculum to connect different interests. A genuine pattern of exploration and self-directed learning may be particularly valuable.Essays & recommendations: Personal essays and teacher/counselor recommendations give context to your achievements and help demonstrate fit with the program.Bioinformatics AnalystComputational BiologistBiostatisticianComputational Neuroscience ResearcherQuantitative BiologistBiological Data AnalystResearch ScientistStatistical AnalystMathematical ModelerScientific Programmer
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