Research Associate in Data Compression in the Intersection of Machine Learning and Information Theory

Imperial College London
London
2 months ago
Applications closed

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


This full-time, fixed-term, in-person postdoctoral position is based at Imperial College’s South Kensington Campus in London, UK, and is funded for up to 23 months, starting in February 2026.



The Research Associate will be jointly supervised by Prof. Deniz Gunduz (Imperial College London) and Prof. Yiannis Kontoyiannis (Cambridge University), and will also have the opportunity to collaborate with Google DeepMind.


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

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.
Design and training of deep neural networks
Implementation of algorithms via computer simulation Experience with programming in Python, C/C++ or another language

Knowledge

Knowledge of information theory, learning theory, optimization methods, and some expertise in recent machine learning 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

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 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 and resources to support your personal and professional .

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