Graduate Teaching Assistant (GTA) - Investigation of Semi-Supervised Solutions in Cloud Detection from Remote Sensing

We are pleased to announce a fantastic opportunity for ambitious computer scientists to join our Computer Science Graduate Teaching Assistant (GTA) Programme!

How does it work?

Candidates will study for a four year, full time funded PhD (3 quarters of your time) whilst working and receiving a salary to gain valuable teaching experience (1 quarter of your time). Candidates will receive a salary and stipend package that exceeds the standard UKRI stipend for a full-time PhD.

Home/RoI Students will have their PhD fees waived, International students will receive a fee waiver equivalent to the Home/RoI fee and will be expected to fund the difference between the International fee and the Home/RoI fee. There will be a package of support to enable you to develop a research career in this exciting field.

PhD Topic: Investigation of semi-supervised solutions in cloud detection from remote sensing.

Earth observation satellite imagery provides earth surface appearance as well as physical properties. However, clouds over the surface (including oceans) negatively affect the observation of optical images. To understand true surface properties, cloud detect is required to identify which pixels within an image are dominated by cloud-free regions, as opposed to cloud dominated pixels. The imagery involved is usually in multiple spectral captured by satellites. The project aims to design and develop algorithms to automatically detect cloud dominated pixels from given satellite images with limited annotated samples in learning/training.

The project aims to apply computer vision and machine learning technologies in cloud detection from remotely sensed imagery by using limited training samples. With respect to the aim, the following objectives are specified.

1. Investigate semi-supervised learning mechanisms in dealing with multi-spectral images.
2. From the computer vision point of view, analyse remotely sensed images with respect to their physical characteristics against image features, which correspond to thick cloud, light cloud, and cloud-free regions.
3. Develop algorithms, combined with findings from computer vision and machine learning, for the cloud detection purpose with effective but limited training samples.

You will need to demonstrate you:

• Meet the academic requirements for a PhD offer from the University of Reading.
• Have a good (1st or 2.1) first degree in Computer Science, Statistics, Data Science, Mathematical Science, Meteorology, Physics or closely related subjects.
• Are able to effectively organise your time and prioritise tasks to balance PhD studies with GTA responsibilities.
• Are able to demonstrate scholarship in developing a publication record in your area of specialist expertise and conduct high quality PhD research.
• Are able to communicate scientific concepts clearly and with enthusiasm and in a way that engages students.
• Have good interpersonal skills and be able to work as part of a team.

How do I apply?

You must upload a combined CV and Proposal in pdf format (max size 1 MB) and complete the supporting statement.

Closing date: 04/042025

Interview: week commencing 21/04/2025 or 23/04/2025

We look forward to hearing from you!

Contact details for advert

Contact Name Dr Hong Wei

Contact Job Title Associate Professor in Computer Science

Contact Email address h.wei@reading.ac.uk

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