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Fully funded PhD Studentship in Energy Networks and Big Data

21 July 2016

Wind turbines Author: Michelle in Ireland, February 2009 http://www.flickr.com/photos/rcvernors/5639342037

About the Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Energy Institute

The Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Energy Institute is a multidisciplinary school within the Bartlett School of Environment, Energy and Resources, with around 70 faculty and staff. It brings together multidisciplinary teams, providing critical mass and capacity for large projects. In particular, the Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Energy Institute develops and undertakes research in the areas of energy-demand reduction and energy systems, to improve energy security and facilitate a transition to a low-carbon economy.

The Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Energy Institute has a Doctoral Training Programme of over 70 PhD students to support the complex and multidisciplinary research objectives of the Institute. Examples of the current diverse range of PhD subjects being studied are at .Ìý

PhD Studentship in Energy Networks and Big Data

The Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Energy Institute invites applications for a fully funded 4-year PhD studentship covering UK/EU fees plus stipend to focus on the use of network and graph based methods, informed by big data, to improve energy efficiency. Analysis is to cross multiple disciplines from transport, considering how to optimise public transport networks, to electricity transmission focusing on grid optimisation to reduce CO2 emissions.  

During the PhD you will be expected to master a broad range of theory including Bayesian statistics, graph theory and machine learning in order to tackle the difficult challenge of network optimisation. Additionally we will be interested in the dynamic behaviour of these networks which will require you to work with large datasets of big data to capture accurately and model. The project provides an opportunity to conduct cutting edge 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 big data and network analysis methods applied to the Energy sector.Ìý

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  • Title: PhD Studentship in Energy Networks and Big Data
  • Supervisors: Dr Aidan O’Sullivan, Lecturer in Statistics, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø EI and Professor Tadj Oreszczyn, Director Bartlett School of Environment, Energy and Resources & .
  • Stipend: approx. £16,000 & UK/EU fees
  • Start Date: October/November 2016
  • Funding Duration: 4 years 
  • Eligibility please check the E
  • You will also have to meet the

Person specification:

  • Passionate about data analysis, modelling, programming and conducting research 
  • An MSc degree in statistics, physics, engineering or other data analysis 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 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, (3) 1-page personal statement outlining motivation, interest and eligibility for the post - should be emailed directly to Mae Oroszlany: e.oroszlany@ucl.ac.uk.Ìý

Stage 2 - Following the interview, the successful candidate will be invited to make a to the Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Research Degree programme. Further guidance will be provided.

Please note that if English is NOT your first language, you will need to provide evidence that you meet the s

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 August 2016.

Interviews week commencing: TBC