MSc Ecology and Data Science
|Start Date||September 2022|
1 year Full Time
|Location||UCL East Campus|
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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.
High-resolution data streams produced from a growing array of sensor technologies such as high-resolution satellite imagery, visual and audio sensor data, geospatial tracking devices and environmental DNA, are revolutionizing how environments are monitored. Additionally, new advances in artificial intelligence and other statistical modelling tools are transforming our ability to analyze these high-resolution data, potentially transforming our understanding of how to manage ecosystems and meet the world’s critical global challenges. However, there is a knowledge and skills gap between ecology and state-of-the-art approaches in data science, sensor technologies and applied artificial intelligence that needs to be bridged to realize this potential.
The new MSc in Ecology & Data Science will directly address this knowledge and skills gap, providing students with a unique and highly sought after expertise, attuned to addressing the critical ecological and environmental global challenges of our time. When making your application to this course, search for it on the system by using the word Ecology. This will bring up the relevant course options on the application system.
- The MSc Ecology & Data Science will be 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.
- Our People & Nature Lab represents an exciting new cross-disciplinary research and teaching partnership to facilitate innovative approaches to tackle the challenges posed by biodiversity loss, global ecosystem degradation and climate change, to support a more sustainable relationship between people and nature.
- UCL’s breadth of expertise across disciplines, the scale of the investment in the new campus combine to create a unique opportunity to take our understanding of the interdependencies of the modern world and its impact upon our environment to the next level.
- UCL’s People and Nature Lab expands the work of the Centre for Biodiversity and Environment Research (CBER) within the Research Department of Genetics, Evolution and Environment. Building on nearly two centuries of the study of the natural environment, CBER was established in 2013 as a world-leading centre of excellence for the study of the impact of rapid environmental change on biodiversity, how species are adapting to anthropogenic change, and how the degradation of nature impacts people and society.
- The MSc Ecology & Data Science is directed by Professor Kate Jones, a world-leading ecologist who has made pivotal innovations in monitoring biodiversity, developing some of the first applied artificial intelligence tools for monitoring wildlife populations. She has also made key advances in modelling and forecasting zoonotic disease outbreaks in humans, breaking down traditional barriers between ecology, climate change and public health to inform global policy.
- The MSc will realise the vision of a new type of programme which addresses the urgent need to produce professionals with expertise in both ecology and data science, and will be taught by a cross-disciplinary team of scientists, including from UCL’s departments of GEE, Computer Science; Geography; Civil, Environmental and Geomatic Engineering; and The Bartlett Faculty of the Built Environment and industry partners from the Zoological Society of London and the Natural History Museum.
- The sustainable management of environmental resources for expanding human populations, and how global climate change and biodiversity targets will be met, are crucial societal challenges of our time. Professionals who can design, implement, and measure the effectiveness of potential solutions to environmental challenges are in demand across a wide range of industries, from sectors such as the built environment, natural environment, and agriculture, to conservation and global policy. This creates a wealth of opportunities for individuals with ecological and environmental knowledge, who can use and apply a wide range of tools in data science and artificial intelligence to address these problems.
This is a new programme launching in 2022, and graduates of the MSc Ecology & Data Science will leave with the project management skills, and theoretical and practical experience needed to implement cutting-edge statistical and computational solutions to address ecological and environmental challenges across society. This in-depth knowledge and experiential skill set will provide you with a unique point of difference that meets a fast-growing need across all industries.
The MSc programme consists of five compulsory modules, one optional module and a research project.
Foundations in Ecology and Ecological Monitoring
Learn key concepts in ecological theory and methods in environmental and biodiversity monitoring.
Develop the fundamental skills you will need to collect, manipulate, visualise and analyse environmental, biodiversity, and citizen science data, using open-source analytical and computational tools.
Technology for Nature
Explore the use, design, deployment and practicalities of different sensor systems for observing and monitoring wildlife populations.
AI for the Environment
Develop advanced analytical skills need to infer and model environmental and biodiversity data, using machine learning and other approaches
Implement new analytical skills within a group dynamic to address a real-world problem partnering with UCL academics or external industry partners.
Foundations of Citizen Science
Foundation knowledge on citizen science and crowdsourcing, covering the theoretical roots of citizen science to its modern application across society and scientific fields
Foundational knowledge on the generation and maintenance of biodiversity, covering topics including phylogenetics, macroecology and biodiversity gradients, and assessment of extinction risk.
MSc. Ecology and Data Science Research Project
A range of projects will be available working with UCL academics and programme partners including the Zoological Society of London, and the Natural History Museum London. Students will carry out an original piece of research that answers an ecological and data science question developed with the student’s expert supervisory team. The student will produce a dissertation detailing and critically analysing their work, and will be expected to prepare an oral presentation delivered to an invited audience.
- Students on the MSc programmes will be taught in the new facilities in the People and Nature Lab at the UCL East campus.
- These facilities include cutting-edge laboratories and workshops, and the ‘Living Laboratory’ of the Queen Elizabeth Olympic Park (QEOP) designed to be home to both people and nature. Networks of sensors in the QEOP collect environmental and biodiversity data and students would have the chance to build and deploy new sensors and analyse the existing data streams.
As well as researchers across UCL departments, students on this programme have the opportunity to work on a research project with academics at The Institute of Zoology Zoological Society of London and the Natural History Museum.
People and Nature Lab's First Project
Whilst the new UCL East campus was being built the People and Nature Lab worked with colleagues at Intel to develop the world’s first automated smart detectors for monitoring bats through their echolocation calls. Our ‘Echo Boxes’ continuously record and identify bat calls using machine learning across the Queen Elizabeth Olympic Park sending the results back in real-time to understand the health of the environment.
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