Job Description
ABOUT THE ROLE
This is a great opportunity to apply advanced data engineering techniques and artificial intelligence tools to develop and deploy an obsolescence data integration platform for gas turbine components. You will be delivering this ambitious innovation project and play a key role delivering the future strategy of Siemens Energy Industrial Turbomachinery Ltd, working with them at their base in Lincoln.
You will lead a transformation project - a Knowledge Transfer Partnership (KTP) - to develop an advanced platform designed for predicting and tracking components obsolescence in gas turbines using AI-driven techniques. Collaborating closely with the team at Siemens Energy Industrial Turbomachinery in Lincoln, you will also work alongside an academic team from the Mechanical and Construction Engineering and Computer and Information Sciences departments at Northumbria University, who will provide support to meet the project aims.
The role is fixed term for a duration of 28 months.
The opportunities available to you:
1. Leading and delivering a challenging and strategic R&D project that directly impacts the business
2. Support from an academic team with specialist knowledge and experience relevant to the project
3. Potential to be retained in a permanent position within the company at the end of the project
4. £4,667 professional training and personal development budget
5. Potential for performance-related salary increments
6. Leadership and Management training from Ashorne Hill
For full details of qualifications, skills and experience required for the post, please review the role description.
APPLICATION SUBMISSION
To apply for this vacancy please click 'Apply Now', and submit:
1. A 2-page CV, highlighting how your skills and experience meet the project criteria (set out in the person specification document).
2. A one-page cover letter outlining relevant projects you have led or worked on.
3. A short video (max 3 minutes): This is your opportunity to tell us how your skills and experience are suitable for the role. For this project, you will be tasked with developing an AI-driven platform to predict and manage component obsolescence in gas turbines. You will work with technologies such as database design, large language models, data integration techniques, and machine learning forecasting models. We are looking for expertise in Python, experience with databases like SQL and data warehouses such as Snowflake, proficiency in data visualisation tools like Power BI/Tableau/etc, as well as experience with machine learning and large language models. Upload the video to your preferred cloud provider (Google Drive, OneDrive, Dropbox, etc.) and include the link to the video clearly in your CV or cover letter.
ABOUT US
Northumbria University is a research-intensive university that unlocks potential for all. We change lives regionally, nationally, and internationally through education and research, tackling the global challenges of our age to transform society and the economy.
Northumbria University is a great place to work. We empower our exceptional people to achieve shared ambitions and promote a positive work life balance. We offer a wide range of benefits including excellent pension schemes, flexible working, a generous holiday entitlement, continued commitment to your learning and development and more.
Northumbria University is committed to creating an inclusive culture where we take pride in, and value, the diversity of our staff. We encourage and welcome applications from all members of the community.
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