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The course leads of MSc READY will be holding an Online Information Session on 13th January 2027 for prospective students. Find out more.

To meet global green energy targets, the number of renewables projects has to increase dramatically over the next two to three decades. Wind, solar, wave and tidal energy continue to grow rapidly every year. Underpinning this rollout is a need for geoscientists equipped with a modern toolkit including coding, machine learning, AI and data science skills. 

This interdisciplinary course will allow you to develop the essential AI and data science skills necessary to solve renewable energy challenges, as well as the geoscience knowledge necessary to apply these skills to the characterisation of the subsurface for renewable energy applications. You will have the opportunity to get hands-on with geophysical surveying equipment, data collection and processing using cutting-edge techniques. The programme is supported by a number of companies in the renewables sector, and you will gain exposure to the renewables industry via guest lectures, seminars and work placement opportunities. 

Find the most recent ‌course information and specifications on the ImperiaMSc READY course page. 

Who is the Renewable Energy with AI and Data Science: Geology and Geophysics (READY) MSc for?

This programme will suit you if you have/are:
• a background in geology, geophysics or other geoscience subject, and wish to learn about programming, data science and machine learning and how these can be used as modern data-driven problem-solving and analysis tools in the renewables sector;
• a strong methodological background in engineering or physical sciences and are wishing to move to, or specialise in, an applied field with an emphasis on subsurface site characterisation for renewable energy applications;
• a professional in the energy industry who would like to develop your skills or wish to transition to the renewables sector

What background in geoscience is necessary for the course?

We do not require prospective students to have any prior geoscience training; we will teach all of the geoscience you need. However, we will look for some interest in geoscience in your application.

What background in programming is required?

All students should have undertaken some programming in a high-level language (e.g. Python, Matlab, C/C++). In the two first weeks you will take a module called Numerical Programming in Python. This provides an introduction to the Python programming language for those new to the language, but is not a first course on programming in general.
We will look for some evidence of prior programming experience in your application. Experience in any high-level language is sufficient, and we can provide pre-course materials to help you develop your Python skills prior to the start of the programme, if required.

What background in Maths is required?

The course includes modules in computational mathematics, data science, machine learning and deep learning, which require some background in mathematics. We would normally expect students to have taken one or more courses as part of their first degree that cover calculus (ideally including ordinary and partial differential equations) and linear algebra (vectors and matrices). Experience equivalent to A Level mathematics may be sufficient, provided that you can demonstrate intuition for solving mathematical problems.

What project can I choose?

Your independent research project can be on any topic in renewable energy, geoscience, or geoengineering, and will contain a substantial computational, data science or machine learning component. A wide range of possible application areas are available. In additional to purely academic projects, your project may be industrial in nature; approximately 50% of our students undertake º£½ÇÉçÇø-hosted projects, with the other 50% hosted by external companies. Students can also arrange their own projects by directly approaching academics in whose research they are interested, or by approaching companies for potential placement opportunities.
Previous project titles include:
• Investigation of Artificial Intelligence Techniques for Boulder Detection in Offshore Geophysical Data
• Hearing Damage: an Exploration of Deep-Learning Detection Methods to Identify Offshore Cable Anomalies
• Machine-Learning-Assisted Geotechnical Characterisation of Subsurface Soils for Offshore Infrastructure
• Cross Regional Automated Mapping of Sub-Circular Depressions for Natural Hydrogen Prospecting
• Quantifying Uncertainty in Inter-Farm Wake Losses for Offshore Wind Farms Under Future Build-Out Scenarios
• Investigating the Feasibility of XGBoost-Based Surrogate Models for Rapid Wind Farm Performance Assessment
• Machine Learning Applications for Seismic Facies Characterisation
• Reinforcement Learning for Norwegian Day-Ahead Hydropower Scheduling
• Foundational GeoAI: Leveraging Visual Language Models for Global Environmental  Mapping And Resilience
• Coupled Geological and Geomechanical Forward Modelling for Sub-Seismic Fault and Natural Fracture Identification

Can I complete a project with an external company?

Yes. We receive project proposals from a large range of companies and start-ups every year. In previous years, these have included:
 
• AIP Invest
• Aramco
• Artio
• Beyond Mining
• BP
• CGG
• Earth Science Analytics
• European Space Agency
• Getech Group plc
• Ineos
• InX Tech
• Net-Zero Geosystems
• North Sea Transition Authority, UK
• SAND Geophysics
• Shell
• SLB
• Sonalis Imaging Ltd.
• SP Global Commodity Insights
• TGS
• TotalEnergies
• Vattenfall
• Venterra
• Weatherford

Are scholarships available for the READY MSc?

You can explore funding opportunities through Department scholarships, º£½ÇÉçÇø’s scholarship search tool, postgraduate grants and scholarships pages, including information about external funding organisations.
Check each award’s eligible courses, entry year, criteria and application deadline. Funding opportunities and application arrangements vary between awards.

Is my background suitable for the Renewable Energy with AI and Data Science: Geology and Geophysics (READY) MSc?

As well as a 2:1 in your undergraduate degree, you will be expected to have some background in mathematics or programming. Geoscience knowledge is desirable but not required, but enthusiasm for studying geoscience is required. 

What will the interview include?

The interview is intended to give candidates an opportunity to find out more about the course from academics leading its design and delivery, as well as to give us an opportunity to learn more about the aspirations and background knowledge of prospective students. We will look for evidence of your background in mathematics and/or programming, and your intuition for solving geoscience problems.

 If you have further queries about the course, please contact the Admin Team at adalovelace-admissions@imperial.ac.uk.