Research Associate – Streaming Health Project
RESEARCH ASSOCIATE – PROJECT ON “Estimating system health from streaming sensor data”
The Research Associate (RA) will develop theoretical stochastic models, liaise with practitioners, and implement proof-of-concept algorithms to estimate the health of engineering systems from sensor data in real-time.
Research Associate – Streaming Health Project
British Library, London
£35,000 per annum (negotiable dependent on skills & experience)
CLOSES 31st August 2017
The goal of this project is the development, theoretical analysis, and proof-of-concept implementation of methods to estimate the health of engineering systems from sensor data in real-time and to make predictions about the system health in the future. Here, the health of an engineering system is defined as the failure probability distribution over all points in time from the current time onwards. The estimation of this distribution poses many challenges of both theoretical and applied nature. For instance, a gradual change in health is the norm, rather than the exception, and traditional anomaly (changepoint) detection methods are often of little use. Another aspect is the selection of meaningful statistics of the future failure distribution to guide maintenance and inspection efforts in real-world systems. We will investigate idealised theoretical models and, concurrently, embark on an intense exchange of ideas with practitioners and applied statisticians to guide the theoretical investigations. While at least in the beginning the emphasis of the project is predominantly on the theoretical side, we will also implement any new algorithms and apply them to data from industry partners.
This project is part of The Turing / LRF programme on Data-centric engineering (PoDCE) and will involve much collaboration with the other projects in this programme. These will take place at the Alan Turing Institute (The Turing) and in the partner universities of University of Warwick, UCL, and Imperial College. At The Turing, access to both a large number of research experts, useful data sets, and cloud computer facilities is available.
The project will be carried out in collaboration with the other project members Saul Jacka (Warwick/The Turing), Aleksandar Mijatovic (KCL/The Turing) and Filip Rindler (Warwick/The Turing).
THE ALAN TURING INSTITUTE
The Alan Turing Institute (the Turing) is the national centre for data science, established in 2015 with the mission to make great leaps in transformational data science research that will have positive real-world impacts.
The Institute has cross-disciplinarily at its core; we bring researchers in mathematics and theoretical computer science, statistics and machine learning, algorithm for data analytics and distributed computing, computational social science and data ethics, and industry partners, to work together in an open and collaborative environment with a shared goal to generate world-class research in data science.
Our researchers are motivated by driving impact, both through theoretical development and application to real-world problems. In our first year we have identified six priority sectors to focus our translational research: Data-Centric Engineering; Defence and Security; Smart Cities; Culture and Media; Financial Services; and Health and Wellbeing.
We have attracted strategic partnerships with a broad range of users of data science including the Lloyd’s Register Foundation, Intel, GCHQ and HSBC. We are looking to develop partnerships with government departments and have recently announced a collaboration with the Office of National Statistics.
We invite you to join us as we grow our research community, supporting our goal to develop the next generation of data science leaders, shape the public conversation, and push the boundaries of this new science for the public good.
The Research Associate (RA) will develop theoretical stochastic models, liaise with practitioners, and implement proof-of-concept algorithms to estimate the health of engineering systems from sensor data in real-time. In the first instance, the RA will work closely with several applied projects to identify the best approach to system health detection that is both interesting to practitioners and translate these findings into stochastic analysis models to be analysed. In a second step, the RA will develop/implement new algorithms. The RA will work with others to perform performance evaluation and comparison with other approaches, and in the preparation of conference and journal papers reporting on the results; to contribute to the ideas in the ongoing project, including looking at potential longer term impact development; and to plan the integration of any new ideas with emerging grant proposals. The position is suitable to candidates who have completed a PhD degree in theoretical or applied mathematics, preferably in the realm of stochastic processes.
The role is available for two years with the possibility of an extension for another year subject to a performance review.
DUTIES & RESPONSIBILITIES
The RA will work with the team (including the investigators, software engineers, data scientists and PhD students) to advance the aims of the project.
- A PhD (or equivalent experience and/or qualifications) in theoretical or applied mathematics.
- An established publication track record commensurate with the career stage of the applicant.
- Programming experience in Python, R, C/C++, Java, or similar.
- Good understanding of stochastic analysis
- Excellent written and verbal communication skills including the ability to present complex or technical information.
- Understanding of data wrangling and data management.
- Ability to lead one’s own work, including planning and execution, and to prioritize work to meet deadlines.
- Ability to work as part of a team.
- Familiarity with resilience engineering and reliability modelling.
- Experience with working with a people from different disciplines.
- Experience in writing grant proposals.
If you are interested in this opportunity, please send your CV and a covering letter to email@example.com. Please also arrange for two references to be sent directly to this e-mail address by the closing date at the latest. Applications will not go forward for shortlisting without references. 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 3339 or email HR@turing.ac.uk.
CLOSING DATE FOR APPLICATIONS: 31th August 2017
INTERVIEWS (at The Turing): 11-14 September 2017
COMMENCEMENT: As soon as possible thereafter
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 status, pregnancy, religion or belief or sexual orientation. Reasonable adjustments to the interview process can also be made for any candidates with a disability.
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.
Full details on the pre-employment screening process can be requested from HR@turing.ac.uk.