About the Project
Mechanical ventilation with heat recovery (MVHR) systems are increasingly used to provide adequate ventilation in well-insulated and air tight dwellings, but often perform very poorly. The research will use validated CFD modelling and empirical date to quantify the impacts of the positioning of MVHR terminals, ductwork and units to reduce exhaust cross-contamination with the objectives of improving indoor air quality and reducing unwanted heat pick-up. Global sensitivity analysis techniques will also be used to identify the critical design parameters. The work will inform the guidance developed by CIBSE, ASHRAE and other institutions interested in improving the performance of MVHR systems.
This research will generate in depth knowledge and the skills needed to address one of the most pressing issues currently facing the built environment. The skills developed are also highly transferable and can be used to further the applicants career in a variety of fields including building performance modelling, data analytics and decision science.
Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Graduate School, including tailored careers advice, to help you succeed in your research and future career.
Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/
School/Dept accolade: We have been ranked 2nd in the UK for Building, and 10th in the UK for Civil Engineering (The Times and Sunday Times Good University Guide 2017)
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We are seeking applicants with good degrees (min 2:1) in computer science or data science, or strongly quantitative degrees with a substantial component of data analysis and programming. Previous experience in, or knowledge of, the energy system is preferable but not required.
The successful candidate is expected to possess the following qualities:
• Demonstrable skills in scientific or data-scientific programming (such as Python, R, C++);
• A strong interest in building performance modelling, computational fluid dynamics and data science applications in the built environment sector;
• A strong interest in transferring knowledge and techniques across disciplines;
• 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. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: Physics, Computer Science, Data Science, Applied Mathematics, Mathematical modelling, Building Performance Engineering
Name: Mrs Lisa Grieve, Administrator LoLo CDT, Loughborough
Email address: [Email Address Removed]
Telephone number: 01509 228540
How to apply
All applications should be made online at http://www.lolo.ac.uk/join-us/how-and-when-to-apply/
Please quote reference number: LoLoCDT18/07
This is a 4-year EPSRC funded studentship with the London - Loughborough Centre for Doctoral Research in Energy Demand based at Loughborough University. The studentship will cover home fees and a tax-free stipend of approx. £16,500 per year for eligible applicants for four years (start date September 2018), along with a substantial budget for research, travel, and centre activities. Applicants should meet the EPSRC eligibility criteria: https://epsrc.ukri.org/skills/students/help/eligibility/