The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.
We are seeking to recruit a postdoctoral research associate to work in the area of uncertainty quantification and inference for energy models of built environments. This post is an appointment to the Digital Twins of Built Environment group in the Data-Centric Engineering Programme at the Alan Turing Institute. You will join a team of researchers affiliated with the Alan Turing Institute supervised by Dr. Ruchi Choudhary (Cambridge, Engineering) and Prof. Mark Girolami (Cambridge, Engineering) and working on a range of projects that respond to the critical carbon challenges of the built environment.
The project builds on ongoing research within the Data-Centric Engineering programme which has been pioneering: (i) the development of Bayesian calibration strategies for large-scale models under sparse data (ii) methods for inference and updating of time-varying parameters in energy models (iii) exploitation of new and diverse forms of data to develop data-centric energy models. The project will involve the development of computational techniques directed towards applications in energy efficient buildings with optimized and seamless integration of observations and energy models.
You will be expected to perform high quality research under the supervision of the principal investigators. Specifically, you will produce breakthrough research in the areas of methods for stochastic energy modelling and uncertainty quantification and contribute to publishing these results in top rated journals and at national and international conferences, as appropriate.
You will possess a PhD in Engineering, Computer Science, or related discipline. You should have a strong background in one or more of the following areas: Energy Simulation and Building Physics, Finite Element Models of Heat Transfer in Buildings, Bayesian Inference, Monte Carlo and Markov Chain Monte Carlo methods.
Informal enquiries may be addressed to Dr. Ruchi Choudhary (email@example.com) or Professor Mark Girolami (firstname.lastname@example.org). Please note that applications sent directly to these email addresses will not be accepted.
Duties and Responsibilities
The research associate will work closely with the project investigators based at the Turing Institute with the aim:
Terms and Conditions
This full-time post is offered on a fixed-term contract for a period of 24 months starting on 1st February 2020 or as soon after that as possible. Happy to Talk Flexible Working.
The salary range offered for this role is £35,000 - £41,000 per annum. A competitive benefits package is also available (https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits).
If you are interested in this opportunity, please click the apply button below and submit your CV, with contact details for your referees and a covering letter.
If you have questions or would like to discuss the role further with a member of the Institute’s HR Team, please contact them on 0203 862 3394 or 020 3862 3357, or email email@example.com. Applicants who would like to submit their application in a different format please email firstname.lastname@example.org.
Closing date for applications: 13 January 2019
Equality Diversity and Inclusion
The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy, religion or belief or sexual orientation. Reasonable adjustments are available to support candidates through the application and interview process. Happy to Talk Flexible Working
Please note all offers of employment are subject to continuous eligibility to work in the UK and satisfactory pre-employment security screening which includes a DBS Check.
|Title||Research Associate - Data Science for Energy Efficient Built Environments|
|Employer||The Alan Turing Institute|
|Job location||British Library, 96 Euston Road, NW1 2DB London|
|Published||December 4, 2019|
|Application deadline||January 13, 2020|
|Job types||Postdoc,   Research assistant  |
|Fields||Statistics,   Energy Technology,   Artificial Intelligence,   Data Mining,   Data Structures,   Databases,   Engineering Physics,   Probability Theory,   Structural Engineering,    and 2 more. Machine Learning,   Stochastics  |