PhD in Engineering: Large-scale real-time data processing and knowledge mining for life cycle built environment design, construction and operation
Sustainable built environment design, construction and operation is inherently multi-objective-oriented; it requires holistic considerations for aesthetics, health, security, safety (structure, fire, earth quake, etc.), resilience, serviceability, adaptability and so on. Therefore, it becomes extremely complex with the superposition of long-term life cycle proactive considerations (e.g. climate changes). BIM (Building Information Modelling) is one of the most important research and industry topics recently emerging in AEC area in terms of its revolutionarily game-changing methodology - from standalone / isolated to inter-connected / integrated working mode by providing standardized industry data format, information and process.
The current major governing computing mode is still standalone-based and that causes fundamental interoperability problems in AEC domain, and makes it extremely difficult to deal with the inter-connected, multi-objectives and complex tasks to achieve sustainable and resilient built environment.The aim of the proposed research is to develop a new generation human-centered innovative computing platform which is 'intelligent' (autonomously executing the prescriptive analysis and generating meaningful and reasonable decision-making alternatives) and 'powerful' (driven by large-scale high-performance computing-based (HPC) distributed optimization that leverages the full potential of Cloud Computing, Internet of Things and Big Data analytics).
How to Apply
In the first instance interested applicants are invited to send a CV and covering email/letter to Engineering-PGR@Cardiff.ac.uk
PLEASE ENSURE THAT YOU QUOTE THE STUDENTSHIP REFERENCE ENG-HL2016 IN THE EMAIL SUBJECT FIELD.
Shortlisted candidates will be invited to submit an online application form.
The deadline for applications is 1 April 2017.
Cardiff University reserves the right to close applications earlier should a suitable candidate be found.