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Research Associate
1 month ago
FTE: 1.0
Term: Fixed to 31 March 2026
Closing Date: 4 August 2024
This is a very exciting opportunity to develop intelligent systems for the prognosis and diagnosis of faults in power network assets. Working closely with a number of different industry partners, this collaboration will create urgently required analytics for accurate and informed decision-making, risk management, and various other functions that will be required for future power network asset management. This will involve experimental design, software development and data science, carrying out research and development of models to predict and diagnose power network asset health condition. Candidates will be expected to have expertise and track record in some or all of the areas listed below. Individuals with complementary expertise will be considered, so please do apply even if you only meet some of the criteria below:
- Power and energy systems – including condition monitoring and asset management of the components of such systems.
- Requirements capture and experimental design.
- Data Science – handling and processing large data sets (experience across multiple domains welcome).
- Artificial Intelligence – including predictive modelling, pattern analysis and recognition.
- Software development and testing experience – ideally in power and energy, but experience in other areas will also be considered.
As a Research Associate, under the general guidance of a PI, 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. Research work will be written up for publication in collaboration with colleagues, and dissemination of the results will be via peer reviewed journal publications and presentation at conferences. You will have the opportunity 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 for the role, candidates will be educated to a minimum of PhD level in an appropriate discipline, or have significant relevant work experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in instrumentation, data capture methods and data analysis methods 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.
Informal enquiries about the post can be directed to Dr Bruce Stephen, Senior Lecturer ) or Professor Brian G. Stewart, Professor of High Voltage, ).
Click here for full details.
£36,024 to £44,263 per annum
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