Research Fellow in Cyber Security and Machine Learning for Smart Grid (041418)

The Department of Computer Science at the University of Surrey is seeking to recruit a full-time researcher to the “SPEAR: Secure and Private Smart Grid” project funded by the European Union as part of the H2020 programme. The successful candidate will join the Secure Systems group (http://www.surrey.ac.uk/cs/research/) working on building attack detection mechanisms and promote resilience operations in smart grids for the H2020 DS-07-2017 project Secure and PrivatE smArt gRid (SPEAR). In summary, the goal of SPEAR is to develop an integrated platform of methods, processes, tools and supporting tools mainly for:

Timely detection of evolved security attacks such as APT, Denial of Service (DoS) and Distributed DoS (DDoS) attacks using big data analytics, advanced visual-aided anomaly detection and embedded smart node trust management. Developing an advanced forensic readiness framework, based on smart honeypot deployment, which will be able to collect attack traces and prepare the necessary legal evidence in court, preserving the same time user private information. Implementing an anonymous smart grid channel for mitigating the lack of trust in exchanging sensitive information about cyber-attack incidents. Performing risk analysis and awareness through cyber hygiene frameworks, while empowering EU-wide consensus by collaborating with European and global security organisations, standardisation bodies, industry groups and smart grid operators.

We are looking for an excellent, motivated, self-driven post-doctoral candidate to conduct high-quality research and gain research experience on big data analytics anomaly detection, modelling of defence-attack smart grid scenarios and recommendation of optimal responses in applications relevant to industrial technologies. 

In addition to supporting the research project with internal and external collaborators, the position will serve as a platform for the research fellow to develop their career and profile as an independent researcher. The potential for the development of knowledge and skills at the intersection of cyber security and machine learning may help the research fellow develop an independent research agenda. The successful candidate will work under the direction of Dr Manos Panaousis and Professor Steve Schneider from the Surrey Centre for Cyber Security.

The Department of Computer Science, within the Faculty of Engineering and Physical Sciences, has an international reputation for research and teaching. Research in the department is focused on two main areas: Secure Systems, and Nature Inspired Computing and Engineering, with Surrey recognized by the National Cyber Security Centre as one of only fourteen Academic Centres of Excellence in Cyber Security Research. Its security related research is focused on protocol analysis, security verification, trusted computing, data privacy, access control, privacy preserving security, cryptography, and distributed ledger technologies and decision-support for cyber security and privacy.

We are looking for applicants who hold, or are near completion of, a PhD in a relevant subject. (Relevant professional experience may be considered.) The successful applicant will demonstrate experience and knowledge of at least one of the following areas:

Big data analytics (e.g. machine learning) Intrusion detection of cyber incidents Smart grid security Mathematical optimisation/Game theory

Good implementation skills are highly desirable.

For informal enquiries please contact Dr Manos Panaousis at e.panaousis@surrey.ac.uk or +44 (0)1483 682651 or Professor Steve Schneider at s.schneider@surrey.ac.uk or +44 (0) 1483 683037.

Please note, it is University Policy to offer a starting salary equivalent to Level 3.6 (£30,688) per annum (full-time) to successful applicants who have been awarded, but are yet to receive, their PhD certificate.  Once the verified original PhD certificate has been submitted to the local HR Department, the salary will be increased to Level 4.1 (£31,604) per annum (full time). 

 

Closing Date: 01 Jul 2018
Category: Research & Teaching