Research Associate in Machine Leaning Methods for Foliage Penetrating Synthetic Aperture Radars

Fixed-term for up to 12 months, until 30^th April 2026. 

Full-time 35 hours per week

The Opportunity:

This Research Associate position will contribute to the project Advanced EO Processing Methods: Foliage Penetration with Long Wavelength SAR within the IDCOM at the University of Edinburgh, which is funded by European Space Agency (ESA) and in collaboration with colleagues at Craft Prospects Ltd. This role is UE07 and is available on a fixed term basis for up to 12 months, until 30^th April 2026.

A full list of main responsibilities and the knowledge, skills and experience required for the role can be found in the full job description below.

Your skills and attributes for success:

• Research background in signal processing, machine learning for signal processing or digital communications, or a closely related area.
• Development experience of open licensed Python/R, or similar, codes for large scale machine learning, using off the shelf packages.
• Familiar with complex datasets and efficient processing methods for information extraction, such as space/air -borne earth-observation data, high-dimensional medical data.
• Working in a team or collaborating with other researchers. Collaboration in the industrial projects or with industry partners is a desirable but not necessary.
• Good track record of generating impacts through publishing academic conference and journal papers, and/or producing popular opensource software packages.

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