"Research Fellow (Sensor Signal Processing) - School of Engineering - 104336 - Grade 7"

Position Details

School of Engineering

Location: University of Birmingham, Edgbaston, Birmingham UK

As this vacancy has limited funding the maximum salary that can be offered is Grade 7, salary £37,099.

Full Time, Fixed Term contract up to June 2025

Closing date: 1st September 2024

Background

Applications are invited for a Research Fellow in cooperative sensor scheduling. The role will involve developing signal processing algorithms for path planning and scheduling of multiple mobile sensing platforms. The Research Fellow will be based in the Microwave Integrated Systems Lab (MISL) at the University of Birmingham and work as part of an international collaboration with researchers in Australia. 

The growth in low-cost sensors and autonomous platforms, result in a need to develop practical algorithms to schedule and plan the actions of groups of such platforms based on sensory information. These algorithms need to cope with complex environments and scenarios that are characterised by multiple, possibly conflicting, tasks. This project seeks to develop a practical solution to the problem that allows long-term planning for a group of autonomous sensing platform. 

The successful application will have a fantastic opportunity working alongside a world leading MISL group at the University of Birmingham. MISL is the largest academic research team in the UK working in radar, remote sensing and signal processing. MISL is a unique collaborative environment delivering world-class cutting-edge research in the areas of radar (quantum enabled, synthetic aperture, forward scatter), space domain awareness, sensors for situational awareness for autonomous platforms, and signal processing and AI-based cognitive sensing.

Role Summary

• You will contribute to the development of a cooperative sensor scheduling algorithm for planning the paths of multiple mobile sensing platform under multiple objectives.
• You will investigate the performance of the above algorithm when considering the number of mobile sensors and how the performance of this algorithm can be characterised when faced with competing objectives.
• Work within specified research grants and projects.
• Operate within area of specialism.
• Analyse and interpret research findings and results.

Main Duties

Specific:

• To develop, implement and evaluate a scheduling algorithm for sensor path planning.
• To engage with project partners regarding the design and integration of the software implementation into the Stone Soup software framework.
• To contribute to the dissemination of the project outcomes through reports to stakeholders and publications of research findings. 

The responsibilities may include some but not all of the responsibilities outlined below.

• Analyse and interpret data
• Apply knowledge in a way which develops new intellectual understanding
• Disseminate research findings for publication, research seminars etc
• Contribute to developing new models, techniques and methods 
• Undertake management/administration arising from research
• Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters 
• Deal with problems that may affect the achievement of research objectives and deadlines
• Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

• PhD (or close to completion) in electronic engineering or related field
• The ideal candidate will have experience in signal processing algorithms
• Ability to programme in python is desirable. 
• Experience working with sensor scheduling algorithms and/or stochastic planning algorithms are desirable. 
• High level analytical capability
• Ability to communicate complex information clearly
• Contribute to the planning and organising of the research programme and/or specific research project
• Co-ordinate own work with others to avoid conflict or duplication of effort

Informal enquiries to Dr Christopher Gilliam, email: c.gilliam.1@bham.ac.uk or Dr Beth Jelfs, email: b.jelfs@bham.ac.uk.