Teesside University
About the Role:
This Knowledge Transfer Partnership (KTP) Associate position focuses on developing an AI-enabled model for automating calibration and fault prediction in draught beer flow lines. You’ll play a vital role in creating a Data as a Service business model through enhanced analytics, working with Vianet Limited and Teesside University.
Key Responsibilities:
- Develop and implement an AI-enabled model for draught beer flow line automation.
- Design and implement solutions for automated calibration and fault prediction.
- Collaborate with business partners to create a data-driven business model.
- Enhance existing analytics solutions for data as a service.
- Contribute to the development and application of Large Language Models (LLMs).
Skills and Expertise:
- Strong understanding of AI principles and algorithms.
- Experience with data analysis and machine learning techniques.
- Proficiency in relevant programming languages (e.g., Python, R).
- Understanding of the hospitality or unattended retail vending sector (beneficial).
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
Job Facilities/Benefits:
- Dedicated training budget for personal development.
- Access to industry-leading technology.
- Supervision from a leading academic research team.
Why Join Us:
This is a unique opportunity to be part of a leading-edge project combining academic research and industry application. You’ll gain valuable experience in a collaborative environment and benefit from opportunities for both personal and professional growth within Teesside University.