Data Scientist / Machine Learning Engineer (KTP Associate)

£31000 - £35000

Manchester, Greater Manchester - 18 months

Apply Now

Job description

An exciting opportunity has become available for a recent graduate to work full time 18-month Knowledge Transfer Partnership (KTP) data scientist/machine learning engineer position in a project to develop a machine learning based solution, combined with timeseries and signal processing techniques, to forecasting dynamic characteristics of centrifugal pumps in large-scale industrial settings. The goal is to use machine learning models to support control systems for more sustainable and cost/resource-efficient operation of the equipment. The project is a spin-off of a short-term Greater Manchester AI Foundry Technical Assist Project. It is likely to have a measurable impact in sustainability and to include some key and well-established stakeholders (e.g., UK’s Environmental Agency).

Employed and supported by an academic team from the University, you will be based at Pumpflow’s premises in Manchester. The post is primarily based at Pumpflow’s sites, but with possibility of flexible work arrangements.

Project description

To develop a remote sensor and accompanying software, allowing end-users to optimise pumping equipment. The unique working principle of the device allows for deployment in both new and existing equipment. This product is not currently available, but global goals of net-zero will bring increased demand for pump efficiency and reliability.

About the business

https://www.pumpflow.net/

Engineering, Machine Learning, AI, Data Science, Computer Science, Mathematics, Physics

Engineering

A first-class BSc in machine learning, data science, computer science, artificial intelligence, statistics, mathematics, physics, or a related, computational science discipline. A postgraduate degree and/or substantial related work experience are highly desirable.

3 June 2024

30 June 2024

7611


An exciting opportunity has become available for a recent graduate to work full time 18-month Knowledge Transfer Partnership (KTP) data scientist/machine learning engineer position in a project to develop a machine learning based solution, combined with timeseries and signal processing techniques, to forecasting dynamic characteristics of centrifugal pumps in large-scale industrial settings. The goal is to use machine learning models to support control systems for more sustainable and cost/resource-efficient operation of the equipment. The project is a spin-off of a short-term Greater Manchester AI Foundry Technical Assist Project. It is likely to have a measurable impact in sustainability and to include some key and well-established stakeholders (e.g., UK’s Environmental Agency).

Employed and supported by an academic team from the University, you will be based at Pumpflow’s premises in Manchester. The post is primarily based at Pumpflow’s sites, but with possibility of flexible work arrangements.