ESRC CASE Studentship for PhD Statistics or Social Statistics: Characterising the influence of stakeholders on building energy consumption
Lancaster University Department of Mathematics and Statistics are offering a fully funded, 3-year PhD position in Statistics or Social Statistics. The position is funded through a CASE studentship at ESRC’s North West Social Science Doctoral Training Partnership and it is in collaboration with an energy data services start-up company, DESCO Analytics. The standard stipend for ESRC studentship covers: full payment of university fees for three years; a tax-free stipend (£14,296p.a. in 2016); and access to a Research Support and Training fund.
Project overview
The recent rise of research on big data has shown that humans play a vital role in building operations, and often represent a bottleneck to better and faster decisions. For example, buildings' energy consumption is affected by the architects choosing the design; by the constructor choosing the types of materials used; by the energy management and maintenance personnel setting the operating thresholds and choosing when to conduct maintenance. All these are tied together by financial decision makers who wish to reach a safe operation with minimum costs. The overall energy consumption of the building is thus the result of a mixture of influences of all stakeholder groups, sometimes with conflicting goals, and design and operating decisions that can be static or change over time. Characterising the influence of stakeholder groups on energy efficiency presents both considerable challenges and considerable opportunities.
While energy data analysis is not new, gaining actionable insight using conventional methods and software suites poses several challenges. Not only is modern data too large in size, it is also fairly complex, and subject to noise. The analysis and interpretation of the results are highly non-standard and span multiple domains. Therefore, in addressing these challenges, the candidate will investigate the use of High-Dimensional Statistics and Functional Data Analysis (FDA) approaches as advanced statistical modelling techniques.
Candidate background
We are seeking a strong and motivated candidate with the following attributes:
Essential
- A MSc degree from a reputable institution in Mathematics, Statistics, Data Science or a related field, obtained by September 2018
- Some background in statistical computing: R, python, Stata, Matlab or C
- Good command of the English language
- Preferably a top 10% finish in class or similar
- Able to work in an international team
- Able to work independently
- Ready to solve problems and proactively ask questions and look for answers
- Flexible to manage the more independent schedule of academia and the fast-paced environment of a start-up
Desired
- Some knowledge of energy vectors and process management preferred
- Experience in working with incomplete, irregular, real-world time series datasets
- Demonstrated people management and interaction skills (e.g. managed a club or a student society, internship or similar experience, etc.)
- Working experience with big data platforms (Hadoop, Hortonworks, Cloudera)
- Experience in working in a Linux environment (Apache, Docker)
Supervisors:
The candidate will be jointly supervised by Dr. Juhyun Park (Mathematics and Statistics) and Dr. Denes Csala (DA data scientist). The supervising team will bring extensive experience in nonparametric regression and smoothing methods, time series data analysis and longitudinal and functional data analysis, energy analytics, complex sociotechnical systems, machine learning and data visualization.
How to Apply:
Submit an application for PhD in Statistics by 15 Feb. 2018:
http://www.lancaster.ac.uk/maths/postgraduate/postgraduate-research/how-to-apply/
In the ‘Personal Statement’, please write one page of your suitability for this research project, headed ‘Characterising the influence of stakeholders on building energy consumption’. All shortlisted candidates will be invited to interview at Lancaster University on 23rd February.
In the first instance, interested candidates are advised to send their CV and transcripts to Dr. Juhyun Park ([log in to unmask]) for advice and further information.
You may leave the list at any time by sending the command
SIGNOFF allstat
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