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Machine learning for demand management within intelligent building energy management systems, with Qbots Technologies Ltd

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  • Full or part time
    Prof Q Ni
    Dr D Csala
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

1 Year Enterprise-led Funded Masters by Research


The objective of this research project is to develop a data-driven model predictive control framework bridging data analytics, machine learning and controls to address the challenge of optimising energy systems operations in buildings. The project will also work on the optimisation of flexible assets like energy storage systems and Vehicle to Grid batteries for reducing the peak demand & enable renewable adoption, while using them for providing balancing services to the grid.

Requirements for the role

 Passionate about energy, big data, machine learning/artificial intelligence, programming and conducting research
 A BSc degree in computer science, statistics, engineering or other quantitative discipline, e.g. machine learning
 Interest in the challenges of the Energy sector of the 21st century
 Knowledge of relevant statistical software or programming languages (such as Python,R, MATLab)
 Ability to use own initiative and prioritise workload
 Good interpersonal and communication skills (oral and written)
 A high level of attention to detail in working methods

Enterprise and collaborative partners

This Masters by Research is a collaborative research project between Lancaster University and Qbots Technologies Ltd. Supervised by Prof. Qiang Ni and Dr Denes Csala of Lancaster University and Dr. Li Yao and Vijay Natajaran of Qbots Technologies Ltd. Qbots is a start-up company aiming to accelerate renewable energy adoption utilising smart energy storage. This is done by using artificial intelligence based algorithms which work for individual businesses by adapting to their energy needs.

Why apply?

By joining the Centre for Global Eco-Innovation you will:
• Receive £15,000 tax free per year
• Receive a contribution of £2,000 towards your tuition fees from your business partner. Tuition fees for 2017-2018 are set as £4,195 for UK/EU applicants and £17,510 for international applicants. Tuition fees for 2018-19 are yet to be set (see university website for published rates by year of entry). Candidates are required to pay the remaining fees up front at the beginning of the project.
• Become part of a cohort of graduates working with an award-winning team on business-led R&D
• Finish in a strong position to enter a competitive job market in the UK and overseas.


Apply Here

To apply for this opportunity please email [Email Address Removed] with:
• A CV (2 pages maximum)
• PhD/Masters Application Form - http://bit.ly/cgephdap
• Application Criteria Document - http://bit.ly/cgephdapcr
• Funded PhD/Masters Reference Form - http://bit.ly/cgephdref

The Centre for Global Eco-Innovation

This doctoral research project is one of a cohort of industry-led funded research projects from the Centre for Global Eco-Innovation, an international alliance supporting university-business collaboration. The Centre delivers high quality, business-led research to create eco-innovative technologies, products and services.

At the heart of the Centre are people who are researching, developing and innovating to address global challenges, including energy, water, natural capital, resource efficiency, food, and waste, to deliver economic, social and environmental benefits. Launched in 2012 the Centre and has won two national awards for its ground breaking approach to sustainable R&D and knowledge exchange.
www.globalecoinnovation.org


Application deadline

Midnight Sunday 18th March 2018
Start date: May 2018

Funding Notes

This project is part funded by the European Regional Development Fund and is subject to confirmation of funding. For further information about the Centre for Global Eco-Innovation please see our website.


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