Key Information

We strive to increase and broaden inclusivity and support everyone, regardless of background, in breaking down any barriers to your application the Department.

If you are unable to pay a course’s application fee, we encourage you to apply for a fee waiver. If you are interested in this MSc and wish to apply for a fee waiver, please contact the Postgraduate Programme Co-ordinator - Thomas Dray - prior to starting your application.

Develop analytical skills in subsurface geoscience and engineering

MSc student Join this 12-month Master’s in Geo-Energy with Machine Learning and Data Science, starting October 2022.

In preparation for the energy transition, you will study subsurface geoscience and engineering, with a focus on data science and machine learning. You will develop skills that can be applied to carbon dioxide storage, water management, hydrocarbon recovery, geothermal energy and other subsurface processes.

The programme will strengthen your understanding of numerical, analytical and computational concepts, and is taught by experts in these areas.

The course is aimed at geoscientists and engineers who want to acquire advanced computational, data science, machine learning and numerical skills relevant to working on various aspects of the energy transition.

ESE's Prof Martin Blunt“Our Master’s in Geo-Energy with Machine Learning and Data Science will equip you with the cutting-edge skills you need to tackle real-world issues facing the global energy sector,” says course director Professor Martin Blunt. “Now more than ever, geoscientists need to gain and apply expertise in Machine Learning and Data Science to problems in subsurface geoscience and engineering.”


Who is the course for?

The MSc in Geo-Energy with Machine Learning and Data Science is suitable for science and engineering graduates, including students with:

  • a mathematics or physical sciences background who want to specialise in subsurface geoscience and engineering, or
  • a geoscience and engineering background who want to learn about data science and machine learning as tools for problem solving and analysis, or
  • a computer science background who wish to expand their knowledge of ML and observational techniques in the context of subsurface energy and storage.

Students are expected to have basic skills in coding and mathematics.  There is a coding course in Python provided before the course formally starts to allow you to refresh and develop your coding skills.

Why should I apply?

The Geo-Energy with Machine Learning and Data Science MSc is unique in combining data science and programming with the fundamentals of geo-energy. It draws on expertise in geo-energy, petroleum geoscience, and petroleum engineering (research and teaching), and you will be taught by Faculty experts in subsurface geoscience and engineering, data science, computational methods and machine learning.

Accordion widget GEMS

Study Programme

The Geo-Energy with Machine Learning and Data Science MSc programme is one of three computational programmes in ESE. The study programme consists of eight taught modules, three mini projects, and one individual research project. It shares teaching modules with our two other computational MSc courses, as shown in the table below.

You will study the following taught courses:

  • Numerical programming in Python
  • Computational Math
  • Data Science and Machine Learning
  • Resource Geology and Geophysics
  • Fluids and Flow in Porous Media
  • Geomechanics and Pressure Analysis
  • Applied Energy Geosciences and Engineering
  • Deep-Learning

You can see the teaching schedule represented visually below. If you would like an accessible version of this information, please contact ESE webmaster.

Courses shared by ACSE, EDSML, and GEMS (ESE MScs)
Courses shared by ACSE, EDSML, and GEMS (ESE MScs). Yellow and purple courses/project modules are shared across MScs
Careers

Graduates of this course will go on to work in academia, or go on to work in:

    • large data and computer companies including start-ups,
    • consultancies offering services to the energy industry and working on natural geo-hazards,
    • the energy industry, including oil, gas and renewables,
    • companies involved in carbon dioxide, hydrogen and/or thermal energy storage,
    • engineering companies involved in the energy transition.

How to apply

Inclusivity

We strive to increase and broaden inclusivity and support everyone, regardless of background, in breaking down any barriers to your application the Department. If you are unable to pay a course’s application fee, we encourage you to apply for a fee waiver. If you are interested in this MSc and wish to apply for a fee waiver, please contact Thomas Dray prior to starting your application.

Scholarship opportunities

 MSc Ada Lovelace Scholarship

We have two departmental scholarships available to women who are offer holders for any of the following programmes, for 2024 entry: 

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 applicants. The Scholarship will cover Home Tuition fees and a stipend. 

How to apply 

To be considered for a Scholarship for one of the above MSc programmes in academic year 2024-25, please apply for the course via the Imperial College MSc graduate course admissions process by 24 May 2024, and complete the scholarship application form by 11am (UK time) on 7 June 2024.

 MSc Scholarship for Home Students

The department has several scholarships available to students who are offer holders for any of the following programmes, for 2024 entry: 

MSc Applied Computational Science and Engineering [contact: Ying Ashton]
MSc Environmental Data Science and Machine Learning [contact: Ying Ashton]
MSc Geo-Energy with Machine Learning and Data Science [contact: Thomas Dray]

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

Scholarships will provide £10,000 towards 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 2024-25, please apply for the course via the Imperial College MSc graduate course admissions process by 24 May 2024, and complete the scholarship application form by 11am (UK time) on 7 June 2024.

MSc + PhD Ada Lovelace scholarship – apply by 30 May 2023

ESE is pleased to offer a departmental scholarship available to women for an MSc plus PhD, for 2023 entry.

The scholarship will be awarded to women who demonstrate exceptional academic merit and/or potential and are open to Home and Overseas applicants.

The Scholarship will cover tuition fees for Home or Overseas students and a bursary for the one-year MSc course, followed by a fully-funded stipend at 3.5 year UKRI (plus 3 years tuition at OS rate) PhD in the Department of Earth Science and Engineering. To be eligible for a scholarship, candidates must fulfil the course’s eligibility criteria and must have submitted an application for the MSc course through the Imperial College MSc programme admissions process including submitting all required documents.

MSc Applied Computational Science and Engineering [contact: Ying Ashton]
MSc Environmental Data Science and Machine Learning [contact: Ying Ashton]
MSc Geo-Energy with Machine Learning and Data Science [contact: Thomas Dray]

To be considered for a Scholarship for one of the above MSc programmes in academic year 2023-24, please:

Your application

We select students on the basis of your academic background, experience, references and personal statement. 

You will need to provide the names of two suitable referees. One must be an academic reference, the second referee may be another academic referee, or where appropriate/relevant, a professional referee.  

Please use your personal statement to describe why you are interested in this course and to highlight your experience that may not be evident elsewhere in the application.  Ensure you speak with your academic referees and ask them to prepare a reference. 

Please note that even if you don’t have prior experience in all of the areas above, but think your background and skills are a good fit for the programme and are excited about developing your skills in data science and machine learning with a strong focus on the energy transition, please don’t hesitate to contact the course administrator to find out more and discuss.

Study at Imperial 

Find out more about postgraduate study at Imperial College London, including tuition fees, scholarships, admissions and how to apply. 

Other funding 

TotalEnergies has a sponsorship opportunity for candidates who are applying for the MSc in Geo-Energy with Machine Learning & Data Science for autumn 2024 entry. See the details and apply for the sponsorship via Total Energies Careers page (view details in French).  Please note that you are required to make an application for study on the MSc GEMS course in addition to making an application for this sponsorship opportunity.

Contact 

Course director: Professor Martin Blunt, Email Professor Blunt

Postgraduate Programme Co-ordinator: Thomas Dray
Department of Earth Science and Engineering
Imperial College London