AI and Machine Learning Researcher – KTP Associate

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.

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