Overview of the role
The project is entitled “Intelligent Management of Multiple Decentralised Solar/Energy Storage Systems” and is joint with OCI and Hanyang University in Korea. The Researcher will engage in internationally leading research in decentralised modelling of dynamic, uncertain, complex systems.

The Machine Learning Research Group is a sub-group within Information Engineering in the Department of Engineering Science of the University of Oxford. The Engineering and Power group is within the same department.

The objective of this 3-year project is to develop a networked, peer-to-peer, decentralised, distributed energy storage system (ESS) for grid energy storage for distributed renewable power generation facilities. The ESS includes an energy management system (EMS) with decentralised prediction of energy supply, energy demand and battery health. The system is designed to be scalable although this project will demonstrate a total of 3 networked ESSes in operation. The predictive algorithms will be built upon sequential Bayesian inference and decision theory. There may be the possibility of a short (e.g.one month) visit to Korea during the course of the project.

Any offer of employment is conditional, subject to the award of the IMBEDS grant to the Department of Engineering Science. Assuming a positive funding outcome, an offer of employment will be extended to the successful candidate in writing after the notification of award status. Please note that in the event that the funding bid is unsuccessful, all conditional offers of employment will be withdrawn.

Responsibilities/duties

You will be responsible for research into

• Predictive modelling of energy supply, energy demand and battery health 
• Scalability of non-parametric Bayesian sequential inference
• Distributed implementations of predictive algorithms
• System integration, verification and validation

Moreover, you will have to:

• Organising regular workshops and project meetings
• Work closely with researchers and industrial partners at the collaborating institutions as well as help supervise DPhil/MEng students in Oxford in furthering the objectives of the project;
• Report regularly on progress to members of the team;
• Write reports on the research and publish these as papers in leading ` conferences and journals;
• Present the results to academic and industrial partners, as well as the public;
• Update and maintain a website for the project;
• The PDRA may have the opportunity to teach (this includes lecturing, demonstrating, small-group teaching, tutoring of undergraduates and graduate students and supervision of masters projects in collaboration with principal investigators). 

Selection criteria 
Essential

• A good first degree in Engineering, Mathematics/Statistics, Computer Science or equivalent, with specialization in probabilistic models.
• Hold (or be close to completion of) a PhD in a relevant area;
• Experience in Bayesian inference, machine learning and practical application in uncertain domains;
• Expertise and experience in computer programming;
• Track record of published work concomitant with experience;
• Ability to work well independently and as part of a team, as well as to possess interpersonal skills necessary to contribute effectively to a collaborative project;
• Ability to communicate scientific ideas to an expert and lay audience, both orally and in writing.

Desirable

• Previous experience with the practical implementation of Bayesian non-parametric models.
• Previous experience of working with probabilistic numeric methods. 
• Previous experience of working in a team with industry
• Evidence of high self-motivation and good organizational skills

How to apply
If you consider that you meet the selection criteria, click on the "Apply Through Website" button and follow the on-screen instructions to register as a user. You will then be required to complete a number of screens with your application details, relating to your skills and experience. When prompted, please provide details of two referees and indicate whether we can contact them at this stage. You will also be required to upload a CV and supporting statement which explains how you meet the selection criteria for the post. The supporting statement should explain your relevant experience which may have been gained in employment, education, or you may have taken time away from these activities in order to raise a family, care for a dependant, or travel for example. Your application will be judged solely on the basis of how you demonstrate that that you meet the selection criteria outlined above and we are happy to consider evidence of transferable skills or experience which you may have gained outside the context of paid employment or education.

Please save all uploaded documents to show your name and the document type.

All applications must be received by midday on the closing date stated in the online advertisement.

Should you experience any difficulties using the online application system, please email recruitment.support@admin.ox.ac.uk

To return to the online application at any stage, please click on the following link www.recruit.ox.ac.uk

Please note that you will be notified of the progress of your application by automatic e-mails from our e-recruitment system. Please check your spam/junk mail regularly to ensure that you receive all e-mails.

Application information: https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form