The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.

Project CHANCE (Coupled Human And Natural Critical Ecosystems). We are seeking to recruit a postdoctoral research associate to work in the area of data science (signal processing, compressed sensing) and machine learning (prediction, explainability) for networked engineering systems. The focus areas include, but are not limited to: water distribution, optical/wireless, transport, and civil networked assets. This post is based in the Data-Centric Engineering Programme at the Alan Turing Institute. You will join a team of researchers affiliated with the Alan Turing Institute supervised by Professor Weisi Guo (Cranfield, Cyberphysical Systems) and work with a wide range of co-supervisors/collaborators including Sir A. Wilson (UCL, Ada Lovelace), Prof. J. McCann (Imperial), Professor I. Guymer (Sheffield), Dr. R. Silva (UCL) & Prof. M. Musolesi (UCL). The CHANCE project is also complemented with Prof. Weisi Guo’s EPSRC CoTRE project – building theoretical and data science foundations to national Digital Twins.

The research has been pioneering: (i) the development of generalised resilience measures for networked dynamical systems [1], (ii) signal processing methods to extract the minimum amount of data in networked dynamical systems [2], and (iii) exploitation of new data science approaches to be applied to infrastructure operators and National Infrastructure Commission (NIC). Our current work was shortlisted for the Bell Labs Prize 2019. The current publications and project webpage can be found at the end of the advert.

The 3-year CHANCE project is coming to the end of its second year, and is looking for a confident and ambitious early-career researcher to join its fledging program. You will be expected to perform high quality research under the supervision of the principal investigator Prof. Weisi Guo. Specifically, you will produce breakthrough research in the areas of methods for graph signal processing and explainable artificial intelligence. You will contribute to publishing these results in top rated journals and at national and international conferences, as appropriate.

You will possess a PhD in Engineering, Computer Science, Statistics or related discipline. You should have a strong background in one or more of the following areas: Signal Processing, Machine Learning, Complex Networks, Bayesian Inference, large-scale simulation and computation methods. Access to Microsoft Azure for accelerated computation will be provided.

Informal enquiries may be addressed to Prof. Weisi Guo ([email protected]). Please note that applications sent directly to this email address will not be accepted.

References

Project Website: https://www.turing.ac.uk/research/research-projects/coupled-human-and-natural-critical-ecosystems-chance

[1] "Resilience or Robustness: Identifying Topological Vulnerabilities in Rail Networks," A. Pagani, G. Mosquera, A. Alturki, S. Johnson, S. Jarvis, A. Wilson, W. Guo, L. Varga, Royal Society Open Science, vol.6(2), Feb 2019: https://royalsocietypublishing.org/doi/10.1098/rsos.181301

[2] "Optimal Sampling of Water Distribution Network Dynamics using Graph Fourier Transform," Z. Wei, A. Pagani, G. Fu, I. Guymer, W. Chen, J. McCann, W. Guo, IEEE Transactions on Network Science and Engineering, 2019: https://ieeexplore.ieee.org/document/8839864

Turing-Lloyds Programme on Data-Centric Engineering

This project will be run as part of the programme for Data-Centric Engineering, based at The Alan Turing Institute. In partnership with the Lloyd’s Register Foundation, the programme brings together world-leading academic institutions and major industrial partners from across the engineering sector. This programme is focused on research in data science, with accompanying translational activities to ensure impact in the field of engineering, as well as education and training components, in keeping with the vision, mission and charitable aims of both the Foundation and the Turing Institute.

Duties and Responsibilities

The research associate will work closely with the project investigators based at the Turing Institute with the aim:

• To establish a sound research base within the Alan Turing Institute in order to pursue individual and collaborative research of outstanding quality, consistent with making a full active research contribution in line with the research strategy outlined by the PIs.
• To write or contribute to publications or disseminate research findings using other appropriate media.
• To attend and present research findings and papers at academic and professional conferences, and to contribute to the external visibility of the Institute.
• To ensure compliance with secure handling of data and health and safety in all aspects of work.
• To participate in and develop internal and external partnerships, for example to identify sources of funding, generate income, obtain projects, or build relationships for future activities.

Essential

• PhD in Engineering, Computer Science, Statistics or a related discipline.
• Expertise in application, development and implementation of signal processing and machine learning techniques for engineering systems.
• Experience in design, development and implementation of research software libraries, ideally using C/C++ and Python and their associated frameworks.
• The ability to work in a team and interact professionally within a team of researchers and PhD students.
• The ability to initiate, develop and deliver high quality research aligned with the research strategy indicated by the PI and any industrial stakeholders and to publish in peer reviewed journals and conferences.
• The ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines.
• A developing track record in producing high quality academic publications.
• Good effective communication (oral and written) skills, presentation and training skills.
• Good interpersonal skills.

Desirable

• Experience in engaging with industry and non-academic partners.
• Ability to aid the PI in writing research proposals.
• Prior experience with simulating large-scale critical engineering systems.

Terms and Conditions

This full-time post is offered on a fixed-term contract for a period of 13 months starting on Spring 2020 or as soon after that as possible. Happy to Talk Flexible Working.

The salary range offered for this role is £35,000 - £41,000 per annum. A competitive benefits package is also available (https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits).

Application procedure

If you are interested in this opportunity, please click the apply button below and submit your CV, with contact details for your referees and a covering letter.

If you have questions or would like to discuss the role further with a member of the Institute’s HR Team, please contact them on 0203 862 3394 or 020 3862 3357, or email [email protected]. Applicants who would like to submit their application in a different format please email [email protected].

Closing date for applications: 15 December 2019

Equality Diversity and Inclusion

The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy, religion or belief or sexual orientation. Reasonable adjustments are available to support candidates through the application and interview process.

Please note all offers of employment are subject to continuous eligibility to work in the UK and satisfactory pre-employment security screening which includes a DBS Check.