Job Description

The role

------------


The Smart Internet Lab is looking for two highly motivated, enthusiastic researchers to research spectrum access techniques, focusing on automated spectrum sharing technologies, looking at both technology enablers and policy consequences for wireless users, vendors, spectrum managers and spectrum regulators.



The successful candidates will carry out research for the JOINER (https://joiner.org.uk ) and HASC (https://allspectrumhub.org/) projects

What will you be doing?

---------------------------


You will work with the JOINER and HASC projects and focus on spectrum access innovation with particular emphasis on automated, spectrum assignment techniques and the creation of a spectrum digital twin. You will also carry out experimental/proof-of-concept implementation work to demonstrate the applicability of your research. Your main research responsibilities may include:


Collect and analyse spectrum data using JOINER-NSF, establishing key patterns and trends in spectrum utilisation and creating automated techniques for detecting and identifying specific signals of interest. Create reference datasets of spectrum usage for the wider community to use as benchmarks for evaluating spectrum sharing techniques. Emulate wireless systems on software defined radio (SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience against different interfering systems. Develop, with colleagues, a spectrum sharing database for use by the JOINER community and design and develop models using AI/ML and other techniques to ensure the efficient but robust sharing of spectrum. Publish research findings in high-impact journals and present at leading conferences.

You should apply if

-----------------------


You have experience and proven track record of

Spectrum Management and Policy

Radio Frequency (RF) Systems: Extensive knowledge on network management and control Software Defined Radio (SDR): Data Analysis and Processing Programming and Software Development AI/Machine Learning (AI/ML): Research and Publication

Additional information

--------------------------

For informal queries, please contact: Professor Dimitra Simeonidou: Dimitra.Simeonidou@bristol.ac.uk

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/

Contract type: There are x 2 positions available - 1 x open ended with fixed funding until 30/09/2026 and 1 x fixed funded until 31/03/2026.

Please confirm in your application which contract type you are interested in.

Work pattern: Full time

Grade: I/J/K/Pathway 2

Salary: Grade I 38,249 - 44,128 OR Grade J 42,882 - 48,149 OR Grade K 49,559 - 55,755 per annum depending on experience

School/Unit: School of Electrical, Electronic and Mechanical Engineering

This advert will close

at

23:59 UK time

on 29/07/25

The interviews are anticipated to take place week commencing 04/08/25

Our strategy and mission

----------------------------


We recently launched our strategy to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an

inclusive working environment where all colleagues can thrive and reach their full potential.

We want

to attract, develop, and retain individuals

with different experiences, backgrounds and perspectives - particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.


JOB NUMBER

ACAD108100

CONTRACT TYPE/WORK PATTERN

Open ended / Full time

POSTING END DATE

29 Jul 2025

FACULTY/DIVISION

Faculty of Engineering

SALARY

38,249-44,128 (Grade I) or 42,882 - 48,149 (Grade J) or 49,559 - 48,149 (Grade K) 49,559 - 55,755 per annum depending on experience