Location: | Newcastle upon Tyne |
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Salary: | £35,000 to £38,000 depending on experience |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 26th June 2024 |
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Closes: | 12th August 2024 |
Job Ref: | 1500 |
ABOUT THE ROLE
Northumbria University in partnership with ROSEN(UK) Ltd are seeking a high-calibre graduate with an MSc (or equivalent) or other Higher Degree in a relevant field such Computer Science or Data Science with a focus on Artificial Intelligence and Machine Learning. You will take a leading role in an ambitious project, developing and testing predictive models for pipeline asset integrity. This project is part of a Knowledge Transfer Partnership (KTP) and you will be working with ROSEN(UK) Ltd at their base in Newcastle upon Tyne (UK), collaborating with an academic team based within the Department of Computer and Information Sciences, Northumbria University.
This is a great opportunity to use cutting edge technical skills in AI and data engineering, including ETL and visualisation, to develop innovative methods for predicting unpiggable gas/oil pipeline conditions identifying features based on advanced anomaly detection and machine learning methods.
You will be delivering an innovation project involving ROSEN(UK)’s complex and diverse dataset of historical pipeline inspections, one of the world’s largest datasets of this type. You will develop an accurate pipeline inspection system based on data science and machine learning technology to implement new services for ROSEN(UK)’s customers.
The opportunities available to you:
For full details of qualifications, skills and experience required for the post, please review the role description.
This role is fixed term for 18 months.
ABOUT THE TEAM
Find out more about ROSEN(UK) Ltd: https://www.rosen-group.com/global/company/explore/we-are/locations/europe/rosen-newcastle/ROSEN-UK-Ltd.html
Find out more about the Department of Computer and Information Sciences at Northumbria University: https://www.northumbria.ac.uk/about-us/academic-departments/computer-and-information-sciences
To arrange an informal phone conversation with one of the project team, please contact:
Dr Ammar Belatreche, ammar.belatreche@northumbria.ac.uk
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