- Phd Studentship In Machine Learning And Cyber Physical Data Stream Analysis Centre For Communication Systems Research Ccsr

Tech
2013-12-07 02:00:32

PhD Studentship in Machine Learning and Cyber-Physical Data Stream Analysis Centre for Communication Systems Research (CCSR)

Deadline

Value of Scholarship

Level of Study

Country Tenable

Renewable

Applications are invited for a funded three-year PhD studentship to investigate the novel techniques and solutions for processing and interpretation of large-scale heterogeneous cyber-physical data streams and extracting human-understandable and machine- interpretable knowledge from raw sensory data. The research work will involve Internet of Things data analysis, machine learning techniques (e.g. probabilistic learning or nature-inspired learning mechanisms), information abstraction and knowledge extraction methods, complex networks and Big Data analytics to process sensory data and extract actionable knowledge from raw observations and measurements.

Candidates should hold a 1st class or 2.1 honours degree in Engineering, Computing, or a related field. Overseas students with equivalent degrees will also be considered. The candidate will preferably have a Masterâs degree with distinction and research backgrounds in one or more of the following areas: Machine Learning, Knowledge and Data Engineering, Internet of Things and Wireless Sensor Networks (WSN), and Semantic Web.

The award will be for a period of 3 years and include Home/Overseas tuition fees plus a stipend (approx Â£13,590 p.a). Applications are welcome from both the UK and internationally.

The student will be jointly supervised by Dr Payam Barnaghi and Prof. Rahim Tafazolli at the Centre for Communication Systems Research at the University of Surrey, UK.

Informal enquiries should be directed to Dr Payam Barnaghi, e-mail: p.barnaghi@surrey.ac.uk

Applications:

Applications should be sent by email to p.barnaghi@surrey.ac.uk. Completed applications should include 1) a curriculum vitae, 2) a statement of research interests (2-3 pages), 3) contact details of two academic referees, and 4) copies of transcripts and certificate of qualifications.

Closing date: 06/01/2014Â

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