Salary range: £36,024 - £44,263
FTE: 1
Term: Fixed (12 months)
Closing Date: 10 July 2024
This is an exciting role aimed to develop AI models than can interpret the composition and behaviour of unknown objects in orbit using spectral, radar and other data sources. The projects form part of a wider venture to develop a range of AI tools for Space Safety and Sustainability, working with institutions such as: University of Arizona, MIT, University of Waterloo, ATI, Nominal Systems, GMV and LMO. This position is based at the University of Strathclyde, Glasgow City Centre campus. Main research objectives are:
O1. Generate time-series spectral data of objects orbiting earth by using a detailed simulator built by the University of Strathclyde. You will also have the opportunity to extend and improve our simulator.
O2. Development of spectral and radar feature extraction techniques for use in neural networks. This can involve using/ developing AI methods to extract salient features of information-rich datasets.
O3. Development and training of neural networks for processing radar and spectra to determine object behaviour, such as attitude. This will build upon the concept of Physics Informed Neural Networks to train models where predictions are constrained by known physical principals.
As a Research Associate, under the general guidance of Dr Paul Murray, you will develop research objectives and proposals, play a lead role in relation to a specific project/s or part of a broader project, conduct individual and/or collaborative research, contribute to the development of new research methods, identify sources of funding, and contribute to the securing of funds for research, including drafting grant proposals and planning for future proposals. You will write up research work for publication, individually or in collaboration with colleagues, and disseminate the results via peer reviewed journal publications and presentation at conferences. You will join external networks to share information and ideas, inform the development of research objectives and to identify potential sources of funding. You will collaborate with colleagues to ensure that research advances inform departmental teaching effort and you will collaborate with colleagues on the development of knowledge exchange activities by, for example, participating in initiatives which establish research links with industry and influence public policy and the professions. You will supervise student projects, provide advice to students and contribute to teaching as required by, for example, running tutorials and supervising practical work. You will contribute in a developing capacity to Department/School, Faculty and/or University administrative and management functions and committees and engage in continuous professional development.
To be considered, you will be educated to a minimum of PhD level in an appropriate discipline, or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in signal & image processing and machine learning / deep learning with excellent programming experience (MATLAB, Python, etc.) and a developing ability to conduct individual research work, to disseminate results and to prepare research proposals. You will have an ability to plan and organise your own workload effectively and an ability to work within a team environment. You will have excellent interpersonal and communication skills, with the ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences.
You may need to travel for technical meetings, experiments (data acquisition) and demonstrations within the UK and internationally. Whilst not essential for the role, applications are welcomed from candidates with: relevant work experience, membership of relevant Chartered/professional bodies (including the Higher Education Academy), experience of relevant student supervision and teaching activities, and/or experience of knowledge exchange related activities.
For informal enquiries, please contact Dr Paul Murray, Reader, paul.murray@strath.ac.uk / 01415482527