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PhD studentship in anticipatory and self-healing infrastructure systems

  • Full or part time
  • Application Deadline
    Monday, September 30, 2019
  • Awaiting Funding Decision/Possible External Funding
    Awaiting Funding Decision/Possible External Funding

About This PhD Project

Project Description

A funded doctoral studentship is available to grow infrastructure systems research which reflects uncertainties due to (i) the burgeoning growth of inter-dependent energy, transport, water, waste and telecoms systems; (ii) the rising abundance of low-carbon distributed infrastructure; and (iii) the digitisation of everything infrastructure related.

The research opportunity will examine the scope and scale of anticipatory and self-healing infrastructure systems. This concerns the exploitation of large data, intelligent algorithms and conditional game theory to allow components of infrastructure to make reasoned and reliable anticipatory recommendations and interventions. These will protect infrastructure services and must act at multiple scales and across diverse geographies. It will herald the next phase of autonomous decision making in inter-dependent infrastructures.

The research will embrace a trans-disciplinary and complex systems perspective, to reflect the multiple disciplines that contribute to infrastructure knowledge and to recognise the co-evolution of sub-systems within the infrastructure ecosystem. You will gain experience of using mixed methods leveraging both quantitative and qualitative data, and you will extend your modelling skills to include novel mechanisms for knowledge identification and autonomy. Multiple social, environmental and economic impacts are possible from this research including: reducing stress and poverty created by the absence of infrastructure services (e.g. mobility, heating); improving the public good through better air quality from increasingly low carbon infrastructures; and maintaining service provision despite weather extremes.

Your research will be conducted in the Infrastructure Systems Institute which provides a supporting environment for skills development and access to a number of on-going and prospective research projects and related industrial and academic partners.

References

Applicants must hold a 1st class or upper 2nd class bachelors or a masters degree in engineering, physics, maths or computer science.

Applicants should send a covering letter and CV to Professor Liz Varga ([email protected]). The successful applicant will then have to apply online to UCL by submitting the PhD application form via https://www.ucl.ac.uk/prospective-students/graduate/apply. Please name Prof Liz Varga as the proposed supervisor.

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