About this role:
This exciting Knowledge Transfer Partnership (KTP) project will develop a novel AI-enabled system to automatically detect low-voltage services and conductors from image data and use sophisticated machine learning models to infer the location of hidden or obscured conductors.
You will work in SSEN’s core asset data team, working collaboratively to develop tools and embed techniques to develop a user-friendly mapping solution.
What you will gain:
- Develop and apply advanced AI and machine learning methods on complex, large-scale data to solve tangible infrastructure problems
- Gain hands-on experience working across multi-disciplinary teams in a large utility company serving 3.9 million customers
- Access a personal development/training budget of £2,000 a year to build further skills relevant to your future career
- Work closely with world-leading researchers at Aston University and receive mentorship and industrial experience
- Contribute to a project expected to deliver major savings and modernisation in electricity distribution, with the opportunity to publish work and attend high-profile conferences
This KTP is a great opportunity for someone keen to plan and deliver business change. You will work with senior University academics and senior company staff on a commercial project which puts the latest research into practice.
What we are looking for:
Skills/ experience required for this exciting role include:
Essential
- Master’s degree (minimum) in Computer Science, Data Science, Computer Vision, Visual Media Engineering, or related subject focused on AI and Machine Learning
- Proficient in AI/deep learning methods, including use of convolutional neural networks
- Experience with analysis of RGB imagery and LiDAR data, particularly with regards to automatic key features extraction and fusion of features
- Skilled in feature extraction
- Programming ability using Python or MATLAB, and familiar with platforms such as Scikit-image, TensorFlow, or PyTorch
Desirable:
- PhD in a related area
- Knowledge of reinforcement learning
- Experience integrating AI/machine learning models into business workflows
- Familiarity with GIS, vectorisation techniques, and statistical tools (e.g. SPSS)
- Understanding of regulatory and safety standards for electrical energy distribution
Attributes:
- Analytical thinker who solves complex technical problems
- Able to articulate business problems, logical solutions and impactful outcomes
- Team player who works productively across locations and disciplines
- Adaptable and comfortable in a hybrid work setting (office-based with travel)
- Proactive learner who makes the most of development opportunities
- Communicates well with both technical and non-technical stakeholders
Additional Benefits and support:
Career prospects:
KTP Associates lead strategic projects, bridging the academic and business worlds, which can enhance and fast-track their career. You will also benefit from expert coaching and mentoring. 60% of our KTP associates are offered employment by their host companies at the end of the KTP.
This is a Knowledge Transfer Partnership (KTP) funded by Southern Electric Power Distribution plc (part of SSEN) and Innovate UK.
KTPs are collaborative, three-way partnerships creating positive impact and driving innovation by linking businesses with the UK's world class knowledge bases to deliver innovation projects led by skilled graduates. It is essential you understand how KTP works and the vital role you will play if you secure this position. To learn more please visit: www.aston.ac.uk/ktp
Aston University: You will work in a project team with Prof Abdul Sadka and Dr Hassan Aqeel Khan from Aston University and the Senior Team members at SSEN with further support from an Innovate UK Knowledge Transfer Adviser.
Location: You will be based predominantly at SSEN in Thatcham with regular visits to the Reading offices and the opportunity to visit Perth Headquarters in Scotland. You will also have access to facilities at Aston University in central Birmingham. Some travel to other sites may also be required.
This role is likely to qualify for endorsement under the Endorsed Funder route of the Global Talent visa. This visa is for talented or promising individuals in academia or research in fields such as science, engineering, medicine, social sciences, or humanities.
See the Home Office guidance: https://www.gov.uk/global-talent
It is an Innovate UK requirement that candidates hold a visa or immigration permission to cover the full duration of the contract. The successful candidate is therefore expected to apply for a visa as necessary in line with their contract duration.
To learn more about this role it is essential you refer to the Job Description documents. For informal enquiries about this role please contact Dr Hassan Aqeel Khan e-mail:, h.khan54@aston.ac.uk
If you think this isn’t the right opportunity for you, please explore other KTP vacancies across the country: https://www.ktp-uk.org/jobs/
Aston University is committed to the principles of the Athena SWAN Charter http://www.ecu.ac.uk/equality-charter-marks/athena-swan . We pride ourselves on our vibrant, friendly, supportive working environment and collaborative atmosphere.
Please visit our website https://jobs.aston.ac.uk/Vacancies.aspx for further information and to apply online.
As users of the disability confident scheme, we guarantee to interview all disabled applicants who meet the minimum criteria for the vacancy.
The University celebrates the rights of freedom of speech and academic freedom and is committed to maintaining and protecting these rights within the law. An offer to work at Aston University will never be denied on the basis of an individual’s lawful expression of their beliefs, ideas or opinions.
Aston University is an equal opportunities employer and welcomes applications from all sections of the community. It promotes equality and diversity in all aspects of its work. We strive to have robust inclusivity strategies in place, to encourage colleagues to have the confidence and freedom to be themselves in the workplace. For more information, visit: https://www2.aston.ac.uk/about/inclusive-aston
Guidance on AI-Assisted Applications
While we cannot prevent applicants from using AI tools to support their application, we ask that all submissions reflect your own experience, achievements, and motivations. We want to understand what you personally bring to the role, so please ensure your application represents your own voice and capabilities.
We recognise the value of flexible working. Please contact the recruiting manager to discuss what flexible working options are available for particular roles.
If you require the job details document or an application form in an alternative format please contact the recruitment team at recruitment@aston.ac.uk