Course summary
Gain the expert skills needed in geology, near-surface geophysics and computation, to characterise the shallow subsurface for a broad range of renewable energy applications. You will examine how data science, numerical methods and machine learning can help solve problems in the renewable energy sector. You will develop an understanding of the geological, geotechnical and geophysical knowledge and data essential to develop ground models for renewables projects. You'll have the opportunity to apply these concepts to real-world settings on an offshore data-collection field trip and through an independent project in an area of your choice. Exposure to industry will be provided through guest lectures, seminars and the option to conduct your independent project in an industry placement. This course is suitable for those from a geoscience, physical science or engineering background looking to advance their computer science skills applied to renewable energy problems. This also includes those in industry looking to transition to the renewables sector.
Entry requirements
2:1 in any geological or physical science or engineering subject. Footnotes Evidence of a good quantitative background (a minimum of a grade A in A-Level Mathematics, or evidence of mathematics programmes in your undergraduate degree) and coding experience are also required. Special cases, based on relevant industrial/professional experience, may be considered in some circumstances.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Imperial College London
South Kensington Campus
Kensington and Chelsea
SW7 2AZ