Applications are invited for a Research Associate position at the Department of Mathematics, Imperial College London. The Research Associate will work at the Alan Turing Institute as part of the Data Centric Engineering Programme. Supervised by Prof Nick Heard and Prof Niall Adams, you will undertake high quality research on developing statistical methods for the Cyber-Security work stream of the Grand Challenge on Monitoring Complex Systems with Rare High Consequence Events. This project is part of a larger Alan Turing Institute programme, funded by the Lloyd’s Register Foundation, performing fundamental research and ground-breaking innovation in the applications of statistical science to improve the performance and allocation of engineering interventions, while developing scientific advances that will have international impact for years to come (https://www.turing.ac.uk/data-centric-engineering/).
Duties and responsibilities
The Cyber-security work stream of the Monitoring Complex Systems with Rare High Consequence Events Grand Challenge aims to develop statistical methodology for monitoring enterprise computer networks for rare events, in particular detecting extreme events potentially corresponding to cyberattacks. The primary objective of the work will be in developing novel Bayesian methods for monitoring network time series. Another aspect of the project will be concerned with data fusion, allowing inferences to be made from combining different sources of cyber data, such as network traffic flow records and host-based process-level data from network hosts. The role may involve working with external collaborators, as well as collaboration with the Alan Turing Institute’s Defence and Security programme and the other work streams of the programme on Monitoring Complex Systems with Rare, High Consequence Events.
The essential requirements for this post are as follows:
- A PhD or equivalent level of professional qualifications and/or experience in Statistics, Machine Learning or a closely related subject
- Background and proven knowledge in some of the following:
- Bayesian modelling
- Network time series modelling
- Data processing and analysis of high volume, complex data
- Computational statistics, developing computationally-scalable methods
- Experience with statistical data modelling, preferably of cyber-security data
- A record of achievement commensurate with your level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations etc
- Excellent written communication skills and the ability to write clearly and succinctly for publication
- Strong computational skills
- Ability to identify, develop and apply concepts, techniques and methods in new contexts
- Ability to keep accurate records of research results and activity, help with reporting
- Ability to exercise initiative and judgement in carrying out research tasks
- Ability to conduct a detailed review of recent literature
- Creative and open approach to problem-solving
- Ability to organise own work independently
- Ability to prioritise own work in response to deadlines
- Ability to work effectively with a team of researchers and across disciplines
- High level analytical capability
- Ability to assess resource requirements and deploy them effectively
- 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.
- Commitment to meeting deadlines
- Commitment to maintaining and enhancing facilities and training others in their use
- Flexible attitude towards work
- Discipline and regard for confidentiality and security at all times
- Willingness to travel both within the United Kingdom and abroad to conduct research and attend conferences/workshops and other meetings.
The position is until 30 September 2022. The expected start date is as soon as is practical.
*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £36,045 – £39,183 per annum.
For any specific queries regarding the post please contact Professor Nick Heard firstname.lastname@example.org
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Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
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For technical issues when applying online please email firstname.lastname@example.org .