|Salary:||£34,189 to £39,609 per annum|
|Placed On:||9th October 2018|
|Closes:||7th November 2018|
Scale 8 - £34,189 to £39,609 per annum together with USS pension benefits
This is a full time, fixed term position until 29/2/2020. This position will be based at the Bay Campus
Main Purpose of the Post
Summary of the overall research programme
Data Mining, Machine Learning (This post) (Main investigators, Dr Xianghua Xie, Professor Mark W. Jones):
There is a clear argument for releasing public data so that commercial companies can create added value by developing apps that can harness the data or utilise the data in existing apps. But there can also be unintended consequences. Therefore, we must strike a correct balance that ensures data releases are safe, secure and do not break privacy and trust, but also provide enough data to produce economic benefits. Organisations that collect and host personal data must be confident about security and privacy. Organisations need a holistic approach to safeguard data release. The close integration of formal modelling, data mining, visual analytics and information security management can solve the complex problem of predicting the impact of releasing data sets.
The group works closely with industrial partners and NHS hospitals. Swansea university also hosts the SAIL databank that curates a wide range of health and population data spanning up to 20 years. The post holder will work closely with researchers in the group on extending a number of newly developed techniques, including deep learning in irregular domain and efficient medical image analysis, and developing new methods for data driven approaches. The key technical objectives include:
(1) Develop interactive data mining methods that allow effective user supervision and efficient knowledge exploitation.
(2) Emloy advanced distributed data mining techniques to detect anomalies and inconsistencies across distributed data in data warehouse at both local level and global level.
(3) Apply developed data mining methods to assess robustness of current data sharing mechanisms and identify robust data sharing strategy in a decentralised, distributed big data environment.
Potential candidates are encouraged to contact the investigators to discuss the position.
For informal enquiries please contact Professor Mark Jones, College of Science at email@example.com or telephone (01792) 513391.
This post will close at midnight 7 November 2018
The University is committed to supporting and promoting equality and diversity in all of its practices and activities. We aim to establish an inclusive environment and particularly welcome applications from diverse backgrounds.
Swansea University is a registered charity. No. 1138342.
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