Renewable Energy with AI and Data Science: Geology and Geophysics (READY) MSc

Renewable Energy with AI and Data Science: Geology and Geophysics (READY) MSc

Join the READY MSc to gain the geology, near-surface geophysics and computational skills needed to characterise the shallow subsurface for a broad range of renewable energy applications.  

To meet the global green energy targets, the number of offshore renewables projects has to increase dramatically over the next two to three decades. Offshore wind is one offshore renewable option, with wave and tidal expected to grow in importance as technology matures. 

This course will provide you with offshore data-collection experience and exposure to industry. 

This course will take you through a curriculum that will enable a deepening of knowledge and skills associated with cutting-edge data science, AI, machine learning and associated computational and observational techniques, and their application to characterisation of the subsurface for renewable energy applications. The programme is currently supported by a number of companies in the Renewables sector who have contributed to curriculum development and will form an industry advisory board to ensure skills being taught match those required for the energy transition.  

Who is the course for?

This programme will suit you if you have/are:

• a background in geology, geophysics or other geoscience subject, and wish to learn about data science and machine learning (the underlying theory/algorithms and how to implement/use them in code) 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 renewables industry who would like to develop your skills in data science and machine learning or are a professional in the oil and gas industry wishing to transition to the renewables sector.

Why should I apply?

This programme is ideal for students looking to gain hands-on experience and work closely with experts in both academia and industry. Throughout the course, you will tackle real-world problems in subsurface site characterisation for renewable energy applications, exploring areas like sedimentary geology, geomorphology, geohazards for engineering, high-resolution geophysics, soil mechanics, and geotechnics.

Collaborative learning is a key part of the course, as you will work alongside peers in applied computer science, data science, and machine learning during classes and project work.

You will also have the opportunity to complete a summer research project, selecting an industry placements or an in-house project supervised by Imperial academics, with options selected based on your preferences.

Scholarship opportunities

MSc Ada Lovelace Scholarship for Women

We have four departmental scholarships available to women who are offer holders for any of the following programmes, for 2025 entry: 

·       MSc Geo-Energy with Machine Learning and Data Science [contact: Thomas Dray]

·       MSc Applied Computational Science and Engineering [contact: Ying Ashton]

·       MSc Environmental Data Science and Machine Learning [contact: Ying Ashton]

·       MSc Renewable Energy with AI and Data Science: Geology & Geophysics [contact: Sophie Pirouet]

To request the scholarship application form, please email the course administrator (name above). 

The scholarships will be awarded to women who demonstrate exceptional academic merit and/or potential and are open to Home and Overseas applicants (3 x Home and 1 x Overseas). The Scholarships will cover Home/Overseas Tuition fees and a stipend.  Additionally for those interested we provide Ada Lovelace PhD scholarship opportunities which will be available to apply for during your Masters year.

How to apply 

To be considered for a Scholarship for one of the above MSc programmes in academic year 2025-26, please apply for the course via the Imperial MSc graduate course admissions process by Friday 28^thMarch 2025 , and complete the scholarship application form by 11am (UK time) on Friday 11^th April 2025.

MSc Ada Lovelace Scholarship for Home Students

The department has four scholarships available to students who are offer holders for any of the following programmes, for 2025 entry: 

·       MSc Geo-Energy with Machine Learning and Data Science [contact: Thomas Dray]

·       MSc Applied Computational Science and Engineering [contact: Ying Ashton]

·       MSc Environmental Data Science and Machine Learning [contact: Ying Ashton]

·       MSc Renewable Energy with AI and Data Science: Geology & Geophysics [contact: Sophie Pirouet]

To request the scholarship application form, please email the course administrator (name above). 

Scholarships will provide full home tuition fees for each successful candidate and will be awarded to candidates who demonstrate exceptional academic merit and/or potential.

How to apply 

To be considered for a Scholarship for one of the above MSc programmes in academic year 2025-26, please apply for the course via the Imperial MSc graduate course admissions process by Friday 28^th March 2025, and complete the scholarship application form by 11.00 am (UK time) on Friday 11^th April 2025.

Imperial's Women in STEM Scholarships

The Women in STEM Scholarships provide support for women studying towards a one-year Master’s degree at Imperial College London commencing in autumn 2025-26

In partnership with the British Council, Imperial College London is offering 5 full scholarships for women who are a passport holder and permanent resident of Brazil.

Find out more about eligibility criteria and how to apply: Women in STEM Scholarships | Study | Imperial College London

How to apply

Applications are accepted online via the Imperial College London Postgraduate website. Find out more about how to apply.

Contact 

For further information please contact ese-msc-ready@imperial.ac.uk.