AI and Machine Learning Researcher - KTP Associate
Role details
Job location
Tech stack
Job description
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.
Requirements
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, Disability Confident About Disability Confident A Disability Confident employer will generally offer an interview to any applicant that declares they have a disability and meets the minimum criteria for the job as defined by the employer. It is important to note that in certain recruitment situations such as high-volume, seasonal and high-peak times, the employer may wish to limit the overall numbers of interviews offered to both disabled people and non-disabled people. For more details please go to .
Benefits & conditions
£2000 per annum for personal and professional development for the duration of the project Annual leave (25 days p/a) Professional support and mentorship Mental Health and wellbeing support: https://www.aston.ac.uk/staff-public/hr/Benefits-and-Rewards/health-wellbeing 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.