Research Associate - Data Science for Energy Efficient Built Environments

Alan Turing Institute London United Kingdom
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Company Description

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.


This project will be run at the intersection of the programmes for Data-Centric Engineering and Urban Analytics, based at The Alan Turing Institute. These programmes are focussed on research in data science, with accompanying translational activities to ensure impact in the field of engineering, as well as education and training components, in keeping with the vision, mission and charitable aims of the Turing Institute.

This post is an appointment to the Digital Twins of Built Environment group in the Data-centric Engineering Program 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 working on projects that respond to the decarbonisation challenge of the built environment. The applicant will be expected to manage collaborations with the Urban Analytics Programme at Turing and engage with relevant stakeholders from government bodies and industry.


The research associates will work closely with the project investigators based at Turing Institute with the aim:

  • To establish a sound research base within the Alan Turing Institute in order to pursue individual and collaborative research of outstanding quality, consistent with making a full active research contribution in line with the research strategy outlined by the PIs.
  • To write or contribute to publications or disseminate research findings using other appropriate media.
  • To attend and present research findings and papers at academic and professional conferences, and to contribute to the external visibility of the Institute.
  • To ensure compliance with secure handling of data and health and safety in all aspects of work.
  • To participate in and develop internal and external partnerships, for example to identify sources of funding, generate income, obtain projects, or build relationships for future activities.


We are seeking to recruit a postdoctoral research associate to work in the area of uncertainty quantification and inference from energy models of buildings, especially high time-resolution models at the city-scale.

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 simulation models of built environments 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 of occupancy. The project will involve the development of computational techniques directed towards applications in energy efficient buildings with specific focus on decarbonisation and human health in buildings.

You will be expected to perform high quality research under the supervision of the principal investigator. Specifically, you will produce breakthrough research in the areas of methods for stochastic energy modelling and strategies for decarbonising heating in buildings 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. Track record of knowledge in Bayesian Inference, Monte Carlo and Markov Chain Monte Carlo methods will be highly advantageous.

Informal enquiries may be addressed to Dr. Ruchi Choudhary ( Please note that applications sent directly to this email address will not be accepted.



  • PhD in Engineering, or an equivalent qualification in Building Physics, Building Energy Simulation, Bayesian Inference or Probabilistic Machine Learning applied to the field of Building Performance (or a closely related discipline).
  • Expertise in application, development and implementation of advanced building energy simulation and/or statistical techniques.
  • Track record of the ability to initiate, develop and deliver high quality research aligned with the research strategy indicated by the PI and any industrial stakeholders and to publish in peer reviewed journals and conferences.
  • The ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines.
  • Good effective communication (oral and written) skills, presentation and training skills.
  • Good interpersonal skills.
  • Teaching may be required as part of the role.
  • Commitment to meeting deadlines.
  • Flexible attitude towards work.
  • Commitment to EDI principles and to the Organisation values.


  • Experience in design, development and implementation of research software libraries, ideally using C/C++ and Python and their associated frameworks.
  • A developing track record in producing high quality academic publications.
  • Ability to write research reports and papers in styles accessible to both academic and lay audiences.
  • The ability to work in a team and interact professionally within a team of researchers and PhD students.

Other Requirements

  • Commitment to meeting deadlines
  • Flexible attitude towards work
  • Commitment to EDI principles and to the Organisation values

Other information


If you are interested in this opportunity, please click the apply button below. You will need to register on the applicant portal and complete the application form including your CV, covering letter and contact details for your referees. If you have questions about the role or would like to apply using a different format, please contact them on 0203 862 3340, or email

CLOSING DATE FOR APPLICATIONS: 13 December 2020 at 23:59


This full-time post is offered on a 2 year fixed-term basis starting 1 January 2021. The annual salary is £35,000-£41,000 (depending on experience) plus excellent benefits, including flexible working and family friendly policies,

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £32,000-£34,000 per annum.

This job description is written at a specific time and is subject to change as the demands of the Institute and the role develop. The role requires flexibility and adaptability and the post holder needs to be aware that they may be asked to perform tasks and be given responsibilities not detailed in this job description.


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 and maternity, religion or belief, sex and sexual orientation. Reasonable adjustments to the interview process can also be made for any candidates with a disability.

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.

Full details on the pre-employment screening process can be requested from