Research Associate* in Machine Learning Aided Data Compression and Communication

About the role

The post is funded by the UKRI AI-Hub INFORMED-AI to explore novel data compression and communication methods building upon information theoretic foundations while exploiting recent advancements in deep learning architectures and training methodologies.

This full-time, in-person postdoctoral position is based at Imperial College’s South Kensington Campus in London, UK, and is funded for up to 18 months, starting in July 2026. 

The Research Associate will be jointly supervised by Prof. Deniz Gunduz and Prof. Pier Luigi Dragotti within the Electrical and Electronic Engineering Department at Imperial College London.

What you would be doing

Key responsibilities include: 

• To take initiatives in the planning of research
• To undertake original research of international excellence
• To ensure the validity and reliability of data at all times
• To maintain accurate and complete records of all findings
• To write reports for submission to research sponsors
• To present findings to colleagues and at conferences
• To submit publications to refereed journals

What we are looking for

Education:

• Research Associate: Hold a PhD in mathematics, engineering, or a related topic.
• Research Assistant: Hold a master’s degree in mathematics, engineering or a related topic and be near completion of a PhD.

Experience

• Practical experience within a research environment and / or publication in relevant and refereed journals
• Practical experience in a broad range of techniques, including,
  • • Optimisation and signal processing methods.
    • Information and coding theory.
    • Communication systems.
    • Design and training of deep neural networks.
    • Implementation of algorithms via computer simulation.
• Experience with programming in Python or C/C++

Knowledge

• Knowledge and research experience in one or more of the following areas: information theory, machine learning theory (in particular generative models), communication systems, signal processing, inverse problems, optimization and compression methods.
• Knowledge of research methods and statistical procedures.

Skills and Abilities

• Ability to conduct a detailed review of recent literature
• Ability to develop and apply new concepts
• Creative approach to problem-solving
• Excellent verbal communication skills and the ability to deal with a wide range of people
• Excellent written communication skills and the ability to write clearly and succinctly for publication

What we can offer you

• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• The opportunity to interact and collaborate with researchers across the INFORMED-AI Hub with regular seminars, training schools, and meetings.
• Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

Please note that job descriptions cannot be exhaustive, and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

For any specific queries regarding the post please contact Prof Deniz Gunduz (d.gunduz@imperial.ac.uk)

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

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