Teaching Fellow in Renewable Energy with AI and Data Science: Geology and Geophysics

About the role:

We are thrilled to invite applicants for a teaching fellow in the broadly defined area of renewable energy site characterisation and data science.  The Department of Earth Science and Engineering at Imperial College London is a key player in the field of sustainable geo-energy, and the application of machine learning to subsurface geology/geophysics. In this context, we are launching a ground-breaking new MSc course in “Renewable Energy with AI and Data Science: Geology and Geophysics (READY)”. This new MSc will be part of the new Ada Lovelace Academy: Delivering gender-balanced post-graduate education in computational subjects to solve the science and engineering challenges of the 21^st century. READY will run alongside three sister courses in “Applied Computational Science and Engineering (ACSE), “Environmental Data Science and Machine Learning (EDSML)” and “Geo-Energy with Data Science and Machine Learning (GEMS)”(see https://www.imperial.ac.uk/earth-science/prosp-students/pg-courses/). The four courses are aligned with Imperial-X (https://ix.imperial.ac.uk/) a major initiative by Imperial College to re-imagine teaching and research for the 21^st century with a focus on the interface between science and digital technologies.

The purpose of this exciting new post is to support the development and teaching requirements of the READY course, but the role will also involve supporting the running and development of existing and potential additional degree programmes.

What you would be doing:

As the new READY teaching fellow, you will be responsible for preparing and delivering lectures, tutorials, problem classes and other training to students in the areas of renewable energy site characterisation (geology and geophysics), data science and machine learning. You will also supervise student projects in these areas, providing advice on study skills and help them with learning problems. This will include assessing the work and progress of students using appropriate criteria and provide constructive feedback to students, including feedback on coursework. You will be able to make a major difference to the course and the department by contributing to the ongoing development and modernisation of computational/data science teaching, and to the integration of modern teaching technology such as automated assessment tools, GitHub Classroom, Microsoft teams, and others. You will work closely with other teaching fellows, and faculty involved in the delivery of our MSc programmes. 

What we are looking for:

We are looking for someone who has:            

• A relevant degree and have, or are nearing completion of, a PhD or equivalent in Geology/Geophysics/Earth Science, Computational Science, Data Science, Machine Learning or a closely related discipline.
• A specialist knowledge in the relevant discipline and of teaching methods and techniques within data science and machine learning

A more exhaustive list of requirements can be found in the job description.

What we can offer you:

• The opportunity to continue your career at a world-leading institution
• Sector-leading salary and remuneration package (including 38 days off a year)

Further Information

This is a full time, permanent position.

Given the teaching-focused nature of the role it will be important to be on-site to interact with students during term-time. However, outside of term times there is potential for remote working.

To apply, visit www.imperial.ac.uk/jobs and search by the job reference ENG03191

Closing date: 1st September 2024

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