Programme Details | |
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Start Date | September entry |
Awards Available | MSc |
Duration | 1 year Full Time 2 years Part Time |
Location | UCL East Campus |
About the course
Biodiversity and ecosystems underpin all human wellbeing and endeavours – from health and happiness to prosperity and security. Yet biodiversity is declining rapidly, with global and local extinctions, and widespread population declines. Meanwhile, land is increasingly under pressure to meet multiple requirements, including the production of sustainable energy, clean water, and healthy, sustainable food. The combined impacts of a growing human population, increasing production and consumption, and global climate change, present an enormous challenge for the management of natural resources and ecosystems.
Facing the twin global challenges of the climate and biodiversity crises, we urgently need to harness the most up-to-date technology to understand how our ecological systems and environmental resources can better be managed.
This programme, the first of its kind to bridge both ecological science and data science, will equip you with a highly valued mix of knowledge, computational and statistical skills, AI expertise, and practical experience of problem-solving approaches to monitoring and managing natural systems.
Learn from experts across UCL, the Zoological Society of London, the Natural History Museum and industry, build your network and prepare to join the next generation of data-savvy biologists addressing time-critical challenges across the natural world.
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What you can look forward to
- The MSc Ecology & Data Science is led by Dr Daniel Maynard, an Associate Professor in Quantitative Ecology at UCL. Daniel's research lies at the intersection of community ecology and macroecology, using a broad array of experimental and statistical approaches to understand how biodiversity is maintained in hyper-diverse ecosystems.
- The MSc Ecology & Data Science is taught in UCL’s purpose-built People and Nature Lab at the new UCL East campus in the Queen Elizabeth Olympic Park in Stratford in East London.
- Develop a rare and sought-after mix of expertise spanning ecology and data science, and build a specialist skillset covering sampling design and biodiversity monitoring methods, sensor design, statistical programming languages like R and Python, and the most up-to-date machine learning and AI tools, including deep learning and computer vision.
- Work with renowned UCL academics from genetics, evolution and environment, robotics, connected environments and geography.
- Gain real-world experience through collaborations with the Natural History Museum and the Zoological Society of London, and project opportunities with industry partners like Chirrup.ai, UKCEH, Biodiversify, East London Waterworks, Google and Microsoft.
- Build the programme around the aspects of ecology and data science that most interest you, with optional specialisms in areas like behavioural ecology, science communication and nature-friendly urban design.
- Gain hands-on experience of design and implementation through a week-long field project in Queen Elizabeth Olympic Park.
Take a look at where you'll be studying
Join us in shaping the future of biodiversity and data science research, and unlock endless opportunities for personal and professional growth in one of the world’s most vibrant and diverse cities.
Take a virtual tour of our campus.
Where the course can take you
You’ll be well equipped to advance the work of government, NGOs, charities and environmentally-aware private sector organisations, or you could apply your expertise within tech or engineering where there’s an ecological agenda. If you’re keen to conduct more indepth research, you could use it as a foundation to a PhD.
Explore some of our biodiversity and data science research
Treemendous: an R package for integrating taxonomic information across backbones. Read more.
Ten simple rules for using large language models in science, version 1.0. Read more.
The global biogeography of tree leaf form and habit. Read more.
Mapping Vulnerable Populations with AI. Read more.
Health and economic impacts of Lassa vaccination campaigns in West Africa. Read more.
How can bottom-up citizen science restore public trust in environmental governance and sciences? Recommendations from three case studies. Read more.
Research Labs at UCL in relevant fields
Students on this programme may have the opportunity to work with one or more of UCL's world-leading research laboratories through the programme or as part of their research project. These are some of the UCL labs across faculties that are relevant to the content taught within this programme.

Prof Tim Blackburn

Dr Tim Newbold

Prof Seirian Sumner

Prof Julia Day