Emory University

What you'll study

• Mathematical modelling: formulation and analysis of deterministic and stochastic models for population dynamics, cellular processes and epidemiological systems.
• Statistical methods for biology: applied probability, statistical inference, experimental design and advanced regression methods tailored to biological datasets.
• Computational tools & programming: practical training in languages and environments commonly used for computational biology (for example Python, R and workflow tools), software development practices and use of high-performance computing resources.
• Genomics and sequence analysis: methods for analysing next-generation sequencing data, variant calling, transcriptomics and functional annotation pipelines.
• Systems biology & network analysis: inference and analysis of biological networks, multi-scale modelling and integration of heterogeneous data types.
• Electives and specialised topics: students can choose from advanced courses in machine learning for biology, structural bioinformatics, metabolomics, or applied epidemiology depending on faculty availability.
• Research or capstone project: supervised independent research or a practicum project that applies quantitative methods to real biological or clinical problems, often carried out in collaboration with Emory research groups or partner institutions.

Entry requirements

Applicants should hold a bachelor’s degree in a relevant discipline such as biology, mathematics, statistics, computer science, engineering or a closely related field. Strong foundation in calculus, linear algebra, introductory probability and statistics, and some programming experience are expected. Prior exposure to molecular biology or genetics is highly desirable for those intending to focus on genomics or bioinformatics. Typical application materials include official transcripts, a personal statement outlining research interests and goals, letters of recommendation, and a curriculum vitae; some applicants may be invited to interview or provide examples of prior quantitative work.

Career prospects

Graduates are prepared for roles in academia, industry and the public sector. Common career paths include computational biologist, bioinformatics analyst, data scientist in biotech or healthcare, research scientist in academic or government laboratories, and positions in clinical informatics. The quantitative and computational skills developed in this programme also provide a strong foundation for doctoral study in computational biology, biostatistics or related fields.

Why study at Emory University

Emory is situated in a major biomedical hub with extensive research activity across basic, translational and clinical science. Students benefit from collaborations with Emory School of Medicine, affiliated research centres and nearby public-health organisations, providing opportunities for interdisciplinary projects and internships. Emory’s faculty include researchers working at the interface of computation and biology, offering mentorship in applied and theoretical problems, while institutional computing resources and core facilities support analysis of large-scale biological data. The programme’s blend of rigorous quantitative training and practical research experience prepares graduates to tackle contemporary challenges in the life sciences.