Data Science for Ecology & Epidemiology
Basic Information
- Course ID
1f784321-3685-4fe3-b702-67a32c526578- Option ID
cfc88531-c117-4881-ba60-20f2a365f03e- Provider
- University of Glasgow
- Type
- postgraduate
- Academic Year
- 2026
- Source
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- Created
- 7/26/2026, 2:26:28 AM
- Updated
- 7/26/2026, 2:26:28 AM
Other Options for this Course
No other options
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"suggest": "Data Science for Ecology & Epidemiology. University of Glasgow. Statistical computing. Data processing. Information technology. Computer science. Ecology. Epidemiology",
"summary": "Become a specialist in the data science of the natural world. Master the advanced statistical and computational skills required to describe complex ecological processes, infer the hidden drivers of disease and biodiversity loss, and predict the impact of interventions to drive global change. The MSc Data Science for Ecology and Epidemiology is an applied programme designed to turn life scientists into quantitative data scientists with the rigorous technical expertise that leading research institutions and conservation organisations highly value.\n\n**WHY THIS PROGRAMME**\n\n\n- The biological sciences are undergoing a data revolution. The challenge is no longer collecting data but the ability to analyse and interpret it. This programme exists to bridge that gap, transforming you into a scientist capable of turning complex biological data into robust evidence.\n\n\n- Join a diverse postgraduate community where your quantitative focus intersects with peers in MSc Conservation Management of African Ecosystems and MSc Animal Welfare Science, mirroring the interdisciplinary teams found in professional research and government agencies.\n\n\n- You will study within the School of Biodiversity, One Health and Veterinary Medicine, surrounded by active researchers working on everything from antimicrobial resistance, disease ecology, and wild immunology to African ecosystem management. This unique environment allows you to apply your quantitative skills to a vast array of real-world biological problems.\n\n\n- Within the School’s diverse portfolio of masters degrees, this programme serves as the dedicated \"quantitative hub\". While other programmes focus on policy, welfare, or management, you will focus on the rigorous analysis and modelling that underpins them all. You will graduate with the elite technical skills required to support and influence the work of field biologists and policy-makers.\n\n\n- We focus on understanding the processes that generate biological data and modelling them effectively. You will gain expertise in Generalised Linear Mixed Models (GLMMs), Machine Learning, Bayesian inference, and Deterministic and Probabilistic Causal frameworks — tools essential for cutting-edge research but rarely taught at this level in generalist biology degrees. While the taught components are delivered in R, we recognise the value of polyglot data science. Depending on your project scope and supervisor, there are opportunities to utilise Python or Julia, particularly for machine learning and computationally intensive modelling.\n\n\n**PROGRAMME STRUCTURE**\n\nThe programme provides a strong grounding in scientific writing and communication, statistical analysis, and experimental design. It is designed for flexibility, to enable you to customise a portfolio of courses suited to your particular interests.\n\nYou can choose from a range of specialised options that encompass key skills in\n- monitoring and assessing biodiversity – critical for understanding the impacts of environmental change\n\n\n- quantitative analyses of ecological and epidemiological data – critical for animal health and conservation\n\n\nAdditional options are available from the other masters programmes offered by our School, providing access to courses on a wide range of topics from animal ethics and legislative policy to African conservation and antimicrobial resistance. A total of 180 credits are required, with 60 flexible credits in the second term. \n\n**CAREER PROSPECTS**\nGraduates of this programme are distinct from general biology graduates. You will be positioned for technical roles that require robust analytical capabilities. Our alumni frequently secure positions such as:\n\n\n- Ecological Modeller\n\n\n- Quantitative Epidemiologist\n\n\n- Biostatistician\n\n\n- Data Scientist for environmental NGOs (e.g., RSPB, BTO) and government agencies (e.g., DEFRA, NatureScot)\n\n\n- PhD Researcher in quantitative biology\n",
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