NOW OPEN: Fully-funded PhD studentship in Artificial Intelligence and Energy

Details

Supervisors: Dr Aidan O’Sullivan, Lecturer in Statistics, UCL EI and Professor Tadj Oreszczyn, Director of Bartlett School of Environment, Energy and Resource.

• Title: PhD Studentship in Artificial Intelligence and Energy
• Stipend: approx. £16,000 & UK/EU fees
• Start Date: September/October 2017
• Funding Duration: 4 years
• Eligibility please check: You need to meet residency requirements. For more information, please follow this link. You will also have to meet the UCL's English Language requirements.

Research Topic

Energy systems are a fundamental component of society that have evolved and changed with new developments and advances in science and technology. Their influence permeates all aspects of our lives, powering homes, industry and transportation. Rapid advances in Artificial Intelligence research have brought technology to the point where disruptive innovation in the Energy Sector is possible, with the potential to completely revolutionise this industry. The energy sector itself is a highly complex system, which faces a multitude of challenges due to the multi-sector multi-vector interactions inherent in a system constrained by. The physics of generation and transmission electricity, social factors affecting demand, spatial and temporal variation in demand, regulatory requirements and the unique challenges of trading in energy markets faced by utilities and network operators. The research in this PhD will focus on how methods in Artificial Intelligence, from neural networks to natural language processing, can be deployed to tackle problems of sustainability within the sector, from improved power flow optimisation, predicting grid congestion, to energy trading modelling and agent based modelling for coordination and decision making.

In your PhD, you will be expected to master a broad range of theory including energy systems, artificial intelligence and machine learning in order to tackle the mathematical and computational challenges associated. The project provides an opportunity to conduct innovative methodological analysis working in collaboration with experts from a number of applied fields of research. You will be comfortable with interfacing with professionals from other disciplines and as your PhD unfolds, become an in-house expert on these methods and their application to the Energy sector. 

Person Specification

• Passionate about energy, artificial intelligence, programming and conducting research
• A MSc degree in computer science, statistics, engineering or other quantitative discipline, e.g. machine learning
• Interest in the challenges of the Energy sector of the 21^st century
• Knowledge of relevant statistical software or programming languages (such as R, MATLab, Python)
• 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

Application Procedure

Stage 1 - Pre-application documents - (1) CV, (2) academic transcripts, and (3) 1-page personal statement outlining motivation, interest and eligibility for the post - should be emailed directly to Yonita Carter: y.carter@ucl.ac.uk.

Stage 2 - Following the interview, the successful candidate will be invited to make a formal application to the UCL Research Degree programme. Further guidance will be provided.

Informal enquiries on the content of the research topic should be emailed to Dr Aidan O’Sullivan, aidan.osullivan@ucl.ac.uk

Deadline for application:  31^st July 2017

Interviews week starting TBC