Fixed term for 2 years, 37 hours per week
We are excited to offer an outstanding opportunity for a skilled and motivated Research Fellow in the field of Drones and Machine Vision for Coastal Infrastructure Monitoring of Railways.
The IRR is a world-class centre for railway engineering research, development, and technology innovation. Our work has helped the industry to reduce operating and maintenance costs, whilst improving reliability and safety. The IRR hosts the UK Rail Research and Innovation Network’s Centre of Excellence in Rolling Stock, and with over £14m of investment in state-of-the-art laboratory facilities, we work alongside our industrial and academic partners to deliver high-impact research across a range of engineering disciplines.
The IRR’s research is particularly relevant to the agendas of safety, sustainability, and carbon reduction. For example, new materials, manufacturing technologies and systems of maintenance and condition monitoring can increase cost-effectiveness for rail operators, and the transition to electrification can be accelerated by research that will make overhead power distribution much more efficient and reliable.
Please visit www.hud.ac.uk/irr for further details on the Institute including a virtual tour of its world-class facilities.
In this role, you will be at the forefront of research and development in the field of railway maintenance and coastal line infrastructure, contributing to the integration of cutting-edge technologies in the industry. Your role will entail tackling the technical challenges associated with integrating Machine Vision into drones, accounting for environmental variations, defect types, and coastal vulnerabilities. Your responsibilities will encompass the collection, processing, and enhancement of data for rolling stock inspections through the utilization of machine vision technology and will extend to experimenting with established state-of-the-art object detection algorithms and exploring the development of customized convolutional neural networks.
A critical aspect of your role will involve conducting real-time testing on a range of edge devices and cloud platforms to evaluate performance. You will also focus on benchmarking and optimizing performance metrics, including inference speed and computational complexity. An additional facet of your work will involve investigating quantization methods to enhance the efficiency of our machine vision systems. Your research findings will be diligently documented, and you will contribute to research publications while also preparing applications for research funding.
This post offers the opportunity to develop a rewarding research career at the University of Huddersfield, working with leading research centres and experts in their field.
With a PhD in Computer/Machine Vision or Drone and Vision, you will have a proven track record of research outputs in reputable journals.
The University is deeply committed to equality and diversity for all its students and staff. We seek to be diverse and inclusive, supporting individuals and groups to fulfil their potential and nurture a sense of belonging. We strive to be an accessible, inclusive employer, removing barriers for all. Find out more about our approach to Equality, Diversity and Inclusion, including our commitments and accreditations as a Disability Confident Employer, Stonewall Top 100 Employer, Athena SWAN Bronze Award holder and our membership of the Race Equality Charter.
If you would like to discuss this opportunity further or have any questions about the role, please contact Dr Muhammad Hussain via email: M.hussain@hud.ac.uk
If you are a current student at the University, you are welcome to apply for part-time roles of 15 hours or less per week, unless you are a part-time postgraduate student, in which case you can also apply for full time roles, subject to any visa requirements.
For more information, please download the recruitment pack.
