AI Data Scientist (KTP Associate)

£35,000 - £38,000

Newcastle upon Tyne, Tyne and Wear - 18 months

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Job description

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.

The opportunities available to you:

– Leading and delivering a challenging and strategic R&D project on AI-based oil and gas pipeline
inspection services for a prominent and globally renowned company.
– Support from an industrial and academic team with specialist knowledge and experience relevant
to the project
– Access to specialised resources and facilities at ROSEN (UK) Ltd and Northumbria University
– Developing expertise in the areas of AI, Machine Learning, anomaly detection for pipeline
inspection
– Potential for a career within ROSEN at the end of the project
– Dedicated travel and training budget for personal and professional development
– Dedicated training time, including leadership and management training at Ashorne Hill
– Publishing key findings in academic journals and presenting them in conferences to increase your
visibility and recognition in this field of expertise.

Project description

Working at the ROSEN offices in Newcastle, you will lead a project with our academics and industry experts at ROSEN to deliver 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.

About the business

ROSEN performs in-line cleaning and inspection services, data analysis, and asset integrity management.

Pipeline Infrastructure

Data Science

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.

9 July 2024

26 July 2024

16 September 2024

1500


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.

The opportunities available to you:

– Leading and delivering a challenging and strategic R&D project on AI-based oil and gas pipeline
inspection services for a prominent and globally renowned company.
– Support from an industrial and academic team with specialist knowledge and experience relevant
to the project
– Access to specialised resources and facilities at ROSEN (UK) Ltd and Northumbria University
– Developing expertise in the areas of AI, Machine Learning, anomaly detection for pipeline
inspection
– Potential for a career within ROSEN at the end of the project
– Dedicated travel and training budget for personal and professional development
– Dedicated training time, including leadership and management training at Ashorne Hill
– Publishing key findings in academic journals and presenting them in conferences to increase your
visibility and recognition in this field of expertise.