|Funding for:||UK Students, EU Students|
|Funding amount:||£14,777 See advert|
|Placed On:||17th January 2019|
|Closes:||15th April 2019|
In situations where quick decisions have to be made during construction, predictions have to be performed in near real time. This can be achieved using computationally efficient meta (surrogate) models. This project is concerned with application and development of novel information technologies and computational models within the Building Information Modelling (BIM) framework for the prediction and quantification of effects induced by construction. Furthermore, optimisation algorithms will be applied for model update and optimisation of process parameters to minimise the effects of the construction on the existing infrastructure. The project will consist of the following steps: i) numerical analysis based on engineering assumptions; ii) generation of meta models based on simulations and available information; iii) system identification using in situ measurements or experiments; iv) prediction of the system behaviour with meta models; and v) steering of process parameters to achieve the desired performance.
Applicants should have, or expect to obtain, a 1st class or 2.1 honours degree (or international equivalent) in Civil Engineering or Computer Science. Candidates should have experience in programming (Python or C++) and preferably also in structural engineering analysis software.
If English is not the candidate’s first language, they must provide evidence that they meet the University’s minimum English Language requirements.
Due to funding restrictions, this position is only available for UK or EU candidates.
The studentship is expected to start on 1st of February.
The studentship covers both tuition fees and a tax-free student stipend at RCUK rates (£14,777 per annum for the 2018/19 academic year).
The duration is 3 years.
How to apply
Informal inquiries can be sent to Dr Jelena Ninic (firstname.lastname@example.org) before submitting an online application. Please send a cover letter and a copy of your CV with your up-to-date relevant experience.
An online application can be made via http://www.nottingham.ac.uk/pgstudy/how-to-apply/how-to-apply.aspx. Please quote the studentship reference and Dr Jelena Ninic.
When applying for this studentship, please include the reference number (beginning with ENG) within the personal statement section of the application. This will help in ensuring your application is sent directly to the academic advertising the studentship.
Name: Dr Jelena Ninic
Type / Role: