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

The University of Edinburgh; City of Edinburgh; On-site; GBP 40,000 - 49,000; Full time

Job summary

An established institution is seeking a Research Associate to contribute to innovative projects in signal processing and machine learning. This role involves working with complex datasets and collaborating with industry partners on cutting-edge research funded by the European Space Agency. Join a vibrant and diverse team, where your contributions will lead to impactful publications and advancements in technology. This position offers a competitive salary and a supportive work environment, making it an exciting opportunity for those passionate about research and development in a collaborative setting.

Benefits

Generous Holiday Entitlement

Defined Benefits Pension Scheme

Staff Discounts

Family-Friendly Initiatives

Flexible Work Options

Qualifications

• Research background in signal processing and machine learning.
• Experience with large-scale machine learning development.

Responsibilities

• Contribute to advanced EO processing methods in a collaborative project.
• Generate impact through publishing academic papers and open-source software.

Skills

Signal Processing

Machine Learning

Digital Communications

Python Development

Data Processing

Team Collaboration

Tools

Python

R

Job description

Grade UE07, £40,497- £48,149 per annum

School of Engineering, College of Science & Engineering

Institute for Imaging, Data and Communications

Fixed-term for up to 12 months, until 30th 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. The project is funded by the European Space Agency (ESA) and in collaboration with colleagues at Craft Prospects Ltd. This role is classified as UE07 and is available on a fixed-term basis for up to 12 months, until 30th 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, digital communications, or a closely related area.
• Development experience with open licensed Python/R, or similar, codes for large-scale machine learning, using off-the-shelf packages.
• Familiarity with complex datasets and efficient processing methods for information extraction, such as space/airborne earth-observation data, high-dimensional medical data.
• Experience working in a team or collaborating with other researchers. Collaboration in industrial projects or with industry partners is desirable but not necessary.
• A proven track record of generating impact through publishing academic conference and journal papers, and/or producing popular open-source software packages.

Click here for a copy of the full job description.

Please apply including a cover letter and CV

What you can expect as a valued member of our team:

• A competitive salary
• An exciting, positive, creative, challenging, and rewarding work environment
• Being part of a diverse and vibrant international community
• Comprehensive staff benefits, including a generous holiday entitlement, a defined benefits pension scheme, staff discounts, family-friendly initiatives, and flexible work options. Details are available on our staff benefits page and our reward calculator can help you discover the total value of your pay and benefits.

Championing equality, diversity, and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to gender equality in higher education. We are members of the Race Equality Charter and Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

Prior to employment, you will need to demonstrate your right to work in the UK. Further information is available on our right to work webpages.

The University can sponsor international workers for this role. If successful, international applicants requiring sponsorship will need to meet the UK Home Office’s English Language requirements and secure a Skilled Worker Visa.

Key dates to note:

The closing date for applications is 16 May 2025. Unless otherwise stated, the application deadline is 11:59pm GMT. For applicants outside the UK, the closing time adjusts to your local time zone.