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Dr H Li, Prof R J Lark
No more applications being accepted
Funded PhD Project (Students Worldwide)
About the Project
For the current infrastructure asset management, one major issue lies on how to leverage the large amount of collected data throughout life cycle and across different sectors including supply chain to provide smart, holistic and proactive decision support towards sustainable infrastructure development and management.
To achieve a step change in infrastructure asset management we propose to develop and apply a high power (Cloud Computing based), intelligent and BIM compliant decision making framework for the "real time operation, maintenance and improvement of a highway network". This will create a flexible and marketable system that will enable Highway Authorities and their Maintaining Agents to meet their statutory duties for safety, while minimising the whole life costs of the assets for which they are responsible and achieving their wider policy objectives.
The project will develop BIM based standards/processes to combine traditional inventory and condition data with the output of condition monitoring and evaluation surveys to provide a basis for the real time performance management, decision making and intervention required to optimise scheme development and prioritise budget limited asset group investment strategies.
The innovation lies in the development of BIM (level 2) standards for infrastructure to facilitate real time and risk based multi-criteria decision making through the processing of large scale "big data" supplied by life cycle multiple stakeholders.
Candidates should hold or expect to gain a first class degree or a good 2.1 and/or an appropriate Master’s level qualification (or their equivalent). Plus ideally have practical experience on construction projects. Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)
The project is targeted at the development of tangible and useable tools along with research outcomes. The chosen candidate is expected to work / program intensively with existing IFC solutions (open BIM – Building Information Modelling - specifications), as well as an in-depth knowledge of Autodesk solutions such as Revit, Civil 3D, hence candidiates should have solid background on BIM.
Candidates should also have:
Either
(1) A Computer science background – with excellent skills on Cloud computing / Big Data analytics / machine learning /data mining / knowledge engineering (ontology modelling); etc.;
or
(2) An Engineering background – with excellent capability for computing, including modelling, numerical simulation/analysis, or optimization algorithm development capability.
The successful candidate will work closely with co-Builder UK (http://cobuilder.co.uk/), e.g. to spend several months / year in industry; Mr. Nick Tune (CEO of co-Builder UK) would be the industry supervisor. The successful candidate will also work with Welsh Government (Transportation department) who will participant from a client point of view as a practical case study. The candidate is expected to work coherently with the existing Cardiff BIM team towards its ultimate scientific vision (http://icompe.engineering.cf.ac.uk).
To achieve a step change in infrastructure asset management we propose to develop and apply a high power (Cloud Computing based), intelligent and BIM compliant decision making framework for the "real time operation, maintenance and improvement of a highway network". This will create a flexible and marketable system that will enable Highway Authorities and their Maintaining Agents to meet their statutory duties for safety, while minimising the whole life costs of the assets for which they are responsible and achieving their wider policy objectives.
The project will develop BIM based standards/processes to combine traditional inventory and condition data with the output of condition monitoring and evaluation surveys to provide a basis for the real time performance management, decision making and intervention required to optimise scheme development and prioritise budget limited asset group investment strategies.
The innovation lies in the development of BIM (level 2) standards for infrastructure to facilitate real time and risk based multi-criteria decision making through the processing of large scale "big data" supplied by life cycle multiple stakeholders.
Candidates should hold or expect to gain a first class degree or a good 2.1 and/or an appropriate Master’s level qualification (or their equivalent). Plus ideally have practical experience on construction projects. Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)
The project is targeted at the development of tangible and useable tools along with research outcomes. The chosen candidate is expected to work / program intensively with existing IFC solutions (open BIM – Building Information Modelling - specifications), as well as an in-depth knowledge of Autodesk solutions such as Revit, Civil 3D, hence candidiates should have solid background on BIM.
Candidates should also have:
Either
(1) A Computer science background – with excellent skills on Cloud computing / Big Data analytics / machine learning /data mining / knowledge engineering (ontology modelling); etc.;
or
(2) An Engineering background – with excellent capability for computing, including modelling, numerical simulation/analysis, or optimization algorithm development capability.
The successful candidate will work closely with co-Builder UK (http://cobuilder.co.uk/), e.g. to spend several months / year in industry; Mr. Nick Tune (CEO of co-Builder UK) would be the industry supervisor. The successful candidate will also work with Welsh Government (Transportation department) who will participant from a client point of view as a practical case study. The candidate is expected to work coherently with the existing Cardiff BIM team towards its ultimate scientific vision (http://icompe.engineering.cf.ac.uk).
Funding Notes
The studentship is open to Home, EU and Overseas candidates, will cover fees at the Home/EU rate, and will provide an annual stipend (£14,296, in 2016/17) for 3.5 years. However, it should be noted that overseas candidates will be required to pay the difference between the home and overseas fee. (Approximately £14,500pa).
In the First instance applicants are invited to send a CV and covering email/letter to [Email Address Removed]
PLEASE ENSURE THAT YOU QUOTE THE STUDENTSHIP REFERENCE HL-PSE-2017 IN THE EMAIL SUBJECT FIELD.
Shortlisted candidates will be invited to submit an online application form and invited to attend an interview.
In the First instance applicants are invited to send a CV and covering email/letter to [Email Address Removed]
PLEASE ENSURE THAT YOU QUOTE THE STUDENTSHIP REFERENCE HL-PSE-2017 IN THE EMAIL SUBJECT FIELD.
Shortlisted candidates will be invited to submit an online application form and invited to attend an interview.