Classic KTP Vacancy advertisement details

Reference: 3824/1

Location: St Austell, Cornwall, PL25 4EJ
Salary: £29,515 to £34,189
Qualification required: Computer Science, Data Science, Maths, Engineering
Closing Date: 05 March 2019
KTP Advert Ref: 3824/1
This post is available immediately on a 2 year fixed-term basis and will be based at BEST company premises in St Austell to support the work of Professor Richard Everson and Dr Jacqueline Christmas on a Knowledge Transfer Partnership (KTP), which is a partnership between the University of Exeter and Best Energy Saving Technology Ltd. (BEST).

BEST is an ambitious, dynamic, high-tech energy management Services Company, which provides energy monitoring and energy saving software, hardware and technical consultancy. Its primary product is Eniscope, a real-time energy management system that disaggregates and processes data on energy consumption and provides real-time and analytic information through graphical displays. Their distribution partners include Quintex, IBM and NG Bailey, and customers/product end-users include Toyota, Shell, Hilton, KFC and McDonalds.

Based in St Austell, on the southern coast of Cornwall, the company's offices are in the region with the highest natural capital value in the UK, which includes Dartmoor and Exmoor National Parks and some of the UK's best beaches and bathing waters.

This project will use machine learning to develop a new energy, building and asset management software product, suitable for use in UK and worldwide markets, with the ultimate aim of improving global energy efficiency. You will research and develop new machine learning algorithms applied to multivariate time-series data. Work is likely to include the following: machine learning of patterns of "normal" usage; using the learned patterns to identify trends and anomalies; incorporating external data sources, such as weather for more accurate prediction; and separating multivariate signals into their constituent independent components.

You will work closely with both the academic team at University of Exeter and BEST to develop and implement the new energy management system.
Skills required: You will be able to:
- Present information on progress and outcomes
- Communicate complex information, orally, in writing and electronically
- Work collaboratively and balance commercial and technical decisions

Applicants must:
- Possess a relevant master's degree (or nearing completion)
- Have a good working knowledge of machine learning and or data science, with experience of software development
- Knowledge of the practical aspects of energy management systems would be advantageous.

Due to the nature of the role, we will only shortlist candidates who clearly demonstrate their suitability for this role via a covering letter and/or personal statement.
Knowledge Base Partner: Exeter, University of
Company partner: Best Energy Saving Technology Limited
Company business area: Provide energy monitoring and energy saving software, hardware and technical consultancy.
Contact: Dr Jacqueline Christmas, University of Exeter,
Stocker Rd,
EX4 4PY, Tel: 01392 723039

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