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MSc Built Environment: Sustainable Heritage (Heritage Science)

  • DeadlineStudy Details: 1 year - 5 years

Masters Degree Description

The Heritage Science route offers research-led, scientific training to tackle heritage challenges through sustainable solutions. This accredited degree combines hands-on learning with technical knowledge and fieldwork, you’ll engage with methods from physical and social sciences, engineering, imaging and computing, developing the skills to protect and understand heritage through cross-disciplinary practice.

Entry Requirements

Normally a minimum of a second-class Bachelor's degree from a UK university or an overseas qualification of an equivalent standard. Applicants with degrees of a lower classification but with considerable senior-level professional experience may also be accepted. Please note that a special qualifying examination may be set. Details of this route can be obtained from the department at the email address at the bottom of this page.

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Fees

For fees and funding options, please visit website to find out more.

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

Students on the Heritage Science route of the Sustainable Heritage MSc graduate with an in-depth understanding of the heritage sector, along with strong scientific expertise to investigate and analyse heritage buildings, collections, and sites.

Module Details

Compulsory modules

  • Dissertation: Sustainable Heritage
  • Introduction to Heritage Science
  • Introduction to Sustainable Heritage
  • Sustainable Heritage in Practice
  • Analytical Methods in Heritage Science
  • Strategies for Sustainable Heritage Buildings and Collections
  • Strategies for Sustainable Landscapes and Natural Heritage
  • Machine Learning for Heritage
  • Climate Change and Heritage
  • Inclusive Urban Heritage

Optional modules

  • Strategies for Sustainable Heritage Buildings and Collections
  • Strategies for Sustainable Landscapes and Natural Heritage
  • Machine Learning for Heritage
  • Climate Change and Heritage
  • Inclusive Urban Heritage

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