Research Associate in Civil and Environmental Engineering
Imperial College London Department of Civil and Environmental Engineering
United Kingdom

Job summary

Invitations are invited for a statistician/data scientist with experience in computationally intensive statistical modelling and/or probabilistic machine learning, based in the Alan Turing Institute, and working as part of the Lloyds Register Foundation / Alan Turing Institute Programme on Data-Centric Engineering, Grand Challenge (GC) 3 on “Data-Driven Design under Uncertainty.”  You will be located in the Department of Civil and...

Job listing information

  • Reference ENG01626
  • Date posted 23 March 2021
  • Closing date 18 April 2021

Key information about the role

  • Location South Kensington Campus (map)
  • Position type Full time, fixed term
  • Salary £40,858 – £48,340 plus benefits
  • Department Department of Civil and Environmental Engineering
  • Category Researcher / Non Clinical Researcher

Job description

Job summary

Invitations are invited for a statistician/data scientist with experience in computationally intensive statistical modelling and/or probabilistic machine learning, based in the Alan Turing Institute, and working as part of the Lloyds Register Foundation / Alan Turing Institute Programme on Data-Centric Engineering, Grand Challenge (GC) 3 on “Data-Driven Design under Uncertainty.” 

You will be located in the Department of Civil and Environmental Engineering at Imperial College and affiliated with the Alan Turing Institute. As the National Institute for Data Science and Artificial Intelligence, the Alan Turing Institute provides a dynamic research environment with state-of-the-art facilities, and the opportunity to interact with the best data scientists from across the UK. It is located in the British Library, and you will need to go through associated screening before starting the role.

The Lloyds Register Foundation / Alan Turing Institute Programme on Data-Centric Engineering is led by Professor Mark Girolami at the Alan Turing Institute.

The programme involves mathematicians, computer scientists and engineers from across Imperial College London. Supervised by Professor Dan Graham and Professor Emma McCoy.

You will undertake high quality research on Data-Driven Design under Uncertainty (GCIII).You will be closely linked to the Department of Mathematics and to the Transport Strategy Centre, led by Professor Graham (co-lead of Grand Challenge II) and the Centre for Systems Engineering and Innovation, led by Professor Whyte (who leads Grand Challenge III), and will engage broadly with the active research communities in data-science at Imperial College London.

The project will develop methodology for modelling complex engineering systems involving “wicked” problems. It will aim to predict system interactions, potential failures and the effect of interventions using the potential of causal inference and machine-learning approaches through both supervised and unsupervised learning.

One potential application of the methodology will be to seek to identify patterns of relevant information and build predictive models to revolutionise the engineering practice of design assurance, which involve checking designs meet standards and requirements.

In this application, the models will be multimodal in nature, fusing a rich and detailed structured dataset of time logs with associated textual design documents. The project is an opportunity to engage with engineers and other experts on a regular basis to progress cutting-edge research that is both suitable for publication into leading academic journals and has impact on the development of data-driven design under uncertainty in complex engineered systems.

The project will serve to connect the work to the other Grand Challenges that make up part of the Programme on Data-Centric Engineering, particularly Grand Challenge II on Monitoring Complex Systems and will have major impact in informing upcoming major infrastructure projects.

Duties and responsibilities

    • To conduct all stages of the analysis of a large multivariate data-set, from extracting relevant data for analysis and identifying appropriate techniques, to reporting new insights and codifying and publishing novel workflows.
    • To interact with a project advisory group made up of engineers, data-scientists and managers involved in the delivery of infrastructure.
    • To detail the research programme to structure the work, agreeing milestones and deliverables and then monitoring and reporting progress against these.
    • To participate with other academic stakeholders in project, Grand Challenge, and Programme related meetings, reviews, workshops, sand-pits, training and teleconferences.
    • To prepare presentations and present the findings in these settings and at international conferences.

Essential requirements

    • PhD (or nearing completion) in computer science, statistics, data science, or in a quantitative field
    • Computer literate with a good knowledge of different computer programs with experience in data presentation and statistical analyses.
    • Knowledge of data analysis methods and how to apply templates and theories to the systematic analysis of secondary data
    • Excellent verbal communication skills and the ability to deal with a wide range of people
    • Willingness to work as part of a team, to be open-minded and cooperative and to align individual work with the overall direction of project

Further information

For informal enquiries about the post please contact Dr Dan Graham at d.j.graham@imperial.ac.uk.

Any queries regarding the application process should be directed to Briony Webb at b.webb@imperial.ac.uk.

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £36,045 - £39,183 per annum.


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