Project Description:

• Apply artificial intelligence to estimate the fine detail of ocean temperature fronts from lower resolution information. Infrared images from satellites do measure the fine spatial details of the temperature of the ocean surface—but only where clouds are not present. Filling in the gaps gives a blurry picture of temperature, whereas there are many reasons to want fine detail everywhere. Use deep learning to solve this problem, using, for example generative artificial intelligence to learn fine ocean structure.

• Find out more about SPIN and explore FAQs here.

Applicant Specification:

• This project is suitable for a numerate undergraduate or postgraduate with some practical knowledge of Python programming: mathematicians, physicists, computer scientists and students of other degrees with significant mathematical, data-analysis or computing experience.

• An underlying interest in the quantitative observation of Earth's environments from space is a desirable motivation, as well as applications of AI.

Minimum requirements:

• Passion and enthusiasm

• Support and advice on the AI and Earth Observation will be available to the applicant, and applicants should have the learning mindset and communication skills to get the best from these interactions for maximising progress.

• Adequate numeracy and computer literacy, ideally including project experience.

Process details:

• 8 weeks minimum fixed term contract to be agreed with successful candidate

• In-person Induction Event to be held on [date], and an in-person/hybrid Showcase Event to be held at the [place/date]

• 5 days holiday to be taken during the placement

This job description set outs the skills and experience we believe are needed to be able to do this job but, research also tells us women are much more likely than men to take this list of requirements as absolute and self-select out of the process. If you think you can deliver this role then we want to hear from you, regardless of the boxes you didn’t tick.