Research Fellow - School of Engineering - 105309 - Grade 7

Position Details

School of Engineering

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £35,880 to £45,163 with potential progression once in post to £47,874

Grade: 7

Full Time, Fixed Term contract up to October 2027

Closing date: 19th February 2025

Background

We invite applications from a highly motivated postdoctoral scientist to deliver automatic classification capability based on machine learning approaches for RSO characterization and anomaly detection using space-borne sub-THz Inverse Synthetic Aperture Radar Imagery.

The researcher will be part of the research team within the Microwave Integrated Systems Laboratory (MISL) and University of Belfast group of Prof. Iain Styles to work on EPSRC funded project Multi-dimensional quantum-enabled sub-THz Space-Borne ISAR sensing for space domain awareness and critical infrastructure monitoring – SBISAR, to create a framework of novel approaches and methods for characterising objects in space.

Role Summary

• Work within specified research grants and projects and contribute to writing bids 
• Operate within area of specialism
• Analyse and interpret research findings and results 
• Contribute to generating funding 
• Contribute to licensing or spin out deals with demonstrated commercial success (such as revenues, asset or company sales, IP generated) and/or public understanding of the discipline or similar
• Apply knowledge in a way which develops new intellectual understanding
• Present research outputs, including (but not limited to) drafting peer-reviewed top level conference and journal papers, or parts thereof, technical reports, create and maintain data or software repositories
• Attend and present results at relevant top-rank conferences to ensure that results are disseminated timely
• Support other research staff, supervise students on research related work and provide guidance/co-supervise PhD students where appropriate to the discipline
• Contribute to broader management/administration processes
• Contribute to exploring and writing new proposals within the area of specialism. 

Main Duties

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

• Develop research objectives and proposals for own or joint research, with assistance of a mentor if required
• Contribute to writing bids for research funding
• Analyse and interpret data
• Apply knowledge in a way which develops new intellectual understanding
• Disseminate research findings for publication, research seminars etc
• Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline
• Contribute to developing new models, techniques and methods 
• Undertake management/administration arising from research
• Contribute to Departmental/School research-related activities and research-related administration
• Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
• Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews
• Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters
• Provide guidance, as required, to support staff and any students who may be assisting with the research
• 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.

Specific Tasks to the post:

• Development, test and validation of algorithms for the classification of satellites and characterization of their state using 2D/3D ISAR images at sub-THz frequencies
• Identify salient features in the images such as specific deployable infrastructure, and changes with respect to reference images
• Investigation and development of suitable algorithms for image and point cloud segmentation to distinguish RSO features based on the statistical and semantic characteristics
• Investigate supervised ML approaches to detect anomalies in RSOs, trained on an ISAR hybrid dataset developed as part of the project
• Investigate unsupervised and supervised ML approaches to teach a model to adapt to unseen observations
• Identify best methods based on key performance indicators and develop tailored algorithms and inference approaches
• Extend the classification of satellites from static images to incorporate information about satellite behaviour. Build full spatio-temporal models of the satellite appearance and dynamics to classify the temporal dynamics of the satellites alongside their appearance
• Assess the space-edge computing requirements and optimize developed approaches accordingly
• Development, test and validation of algorithms for the characterization of space debris of different nature (manmade, natural) using 2D/3D ISAR images at sub-THz frequencies
• Investigate detection and imaging capabilities of the developed approaches suitable for characterization of clusters of space debris.

Person Specification

• PhD (or near to completion) qualification in the fields of ML, radar image processing, signal processing, classification in radar-based remote sensing. Degree in computer science, physics, electrical engineering or a related discipline (or equivalent qualifications) are expected with experience in ML-based data processing 
• Demonstrable experience in development and application of machine learning techniques for image processing and analysis is essential
• Strong background in radar, signal processing and related technologies is highly desirable 
• Fluency in relevant models, modelling techniques or methods and ability to contribute to developing new ones 
• Demonstrated ability to document and communicate work effectively to a variety of audiences
• Ability to assess resource requirements and use resources effectively 
• High level analytical capability
• Ability to communicate complex information clearly
• Understanding of and ability to contribute to broader management/administration processes.

Informal enquiries to Professor Marina Gashinova, email: m.s.gashinova@bham.ac.uk 

We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. You can find out more about our work to create a fairer university for everyone on our website.