Presbyterian College

What you'll study

This interdisciplinary programme combines foundational courses in mathematics, statistics and computer science with molecular and cellular biology, genetics and laboratory techniques. Core components typically include differential equations, linear algebra, probability and mathematical modelling; programming and data structures (often in Python and R); statistical inference and machine learning; molecular biology, genetics and genomics; and bioinformatics methods for sequence analysis, comparative genomics and structural biology.

• Foundational mathematics: calculus, linear algebra, differential equations and mathematical modelling for biological systems.
• Computing and data science: programming, algorithms, databases, statistical computing and applied machine learning for biological data.
• Biological sciences: cell and molecular biology, genetics, biochemistry and laboratory techniques including wet-lab skills important for interdisciplinary research.
• Bioinformatics and computational biology: sequence analysis, genome assembly and annotation, comparative genomics, proteomics, structural bioinformatics and systems biology.
• Capstone and research: an integrative senior capstone or honours project that applies computational methods to a biological question, often involving independent research under faculty supervision.
• Electives and practica: opportunities to take advanced electives (for example in population genetics, epidemiological modelling, or advanced machine learning), internships with industry or research groups, and cross-disciplinary courses in ethics or scientific communication.

Students gain practical experience with common tools and languages used in the field (such as Python, R, command-line bioinformatics tools and version control) and develop skills in data management, reproducible research and scientific communication.

Entry requirements

Applicants should have a high school diploma or equivalent with a strong background in mathematics and science. Recommended preparation includes courses in calculus, biology and chemistry; prior exposure to computer science or programming is strongly encouraged. Typical application materials include a completed application, official school transcripts, a personal statement, and one or more academic references.

Presbyterian College considers applicants holistically; demonstrated readiness for rigorous quantitative and laboratory work, such as high grades in relevant subjects, AP/IB credits where applicable, programming experience, or participation in science/math extracurricular activities, will strengthen an application. Transfer students should provide college transcripts and may receive credit for prior coursework in mathematics, science or computing.

Career prospects

Graduates are prepared for a range of careers that bridge biology and quantitative analysis. Common pathways include roles as bioinformatics analysts, computational biologists, data scientists in biotechnology and pharmaceutical companies, and research technicians in genomics or systems biology labs. The degree also provides excellent preparation for graduate and professional study—master’s and PhD programmes in computational biology, bioinformatics, biostatistics and related fields, as well as professional programmes in medicine and public health.

Alumni find positions in academic research groups, biotechnology startups, healthcare analytics teams, public health agencies, and companies specialising in genomic services or computational drug discovery. The programme’s emphasis on interdisciplinary training, programming skills and hands-on research experience helps graduates be ready for both entry-level technical roles and advanced study.

Why study at Presbyterian College

Presbyterian College offers a liberal arts environment with small class sizes and close faculty mentorship, which is particularly beneficial for interdisciplinary, research-focused degrees. Students have access to personalised advising, opportunities to engage in undergraduate research from early in their studies, and capstone projects that foster close collaboration with faculty mentors. The college’s curriculum emphasises communication and ethical reasoning alongside technical skills, preparing students to work in collaborative scientific teams.

Practical training is supported by laboratory courses and computing resources, and students can pursue internships and research placements to gain real-world experience. The college’s setting and alumni network also support regional internship and employment opportunities in the life sciences, while the programme’s quantitative emphasis equips students to adapt to evolving careers in computational biology and data-driven biotechnology.