PhD Position in Machine Learning for Multidimensional Data at University of Sheffield

One PhD scholarship in Machine Learning for Multidimensional Data is available at Department of Computer Science, University of Sheffield, UK.
-The Scholarship/Funding
This is a full scholarship for UK/EU applicants, covering tuition fees and standard living costs. For other applicants, the same amount of scholarship is available but they have to find additional financial support to cover the difference between home fee and international fee. Additional funding opportunities are available at http://www.sheffield.ac.uk/dcs/resdegrees/funds
-Date
This position will be open until filled with preferred starting date in September/October 2017.
-Research Topic
The PhD research project will focus on machine learning methods for big multidimensional data (i.e., tensors) with applications in brain imaging, neuroscience, medical imaging, and beyond. Within this scope, the project will be tailored to the interest and technical strength of the candidate.
Examples of learning methods include component analysis (PCA, ICA, CCA, LDA, PLS) and their nonlinear/probabilistic/scalable extensions for dimensionality reduction and feature extraction, sparsity-constrained models for regression and feature selection, and low-rank/generalized models for matrix/tensor completion.
Examples of applications include fMRI analysis for brain state decoding or brain disease detection/classification, lung MRI analysis for pulmonary vascular disease studies, EEG signal analysis for brain?computer interface or brain disease detection/classification, recommender systems, and computer vision.
-Candidate Requirements
The candidate is expected to have solid mathematical background, strong programming skills, and keen interest in high-impact research work. Relevant experiences and publications in the methods and/or applications above are preferred. These are in addition to the official requirements that must be satisfied (2nd upper/above, English). Please refer to the FAQ at
https://www.sheffield.ac.uk/postgraduate/research/...
-How to Apply
Applicants should first email h [dot] lu-AT-sheffield [dot] ac [dot] uk directly with one zip file "FirstName_LastName.zip" including the following:
1. CV (including GPA/ranking, up to two pages).
2. Personal statement (up to one page with a brief description on why you want to apply).
3. Representative papers (up to three, at least one).
4. Non-UK/EU only: please indicate your source of funding to cover the fee difference.
Qualified candidates will then be contacted for further consideration and the selected candidate will be guided through the formal application process.
-The Supervisor
Dr Lu is now a Lecturer in Machine Learning at the Department of Computer Science, the University of Sheffield. He received his PhD degree from the University of Toronto, Canada, in 2008, and the MEng and BEng degrees from Nanyang Technological University, Singapore, in 2004 and 2001, respectively.
His current research focuses on machine learning, brain imaging, and tensor analysis. His research also covers related areas such as big data, biomedical engineering, computer vision, and signal/image processing. He is the leading author of the book "Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data" (CRC Press, 2013). He is the recipient of the 2013 IEEE Computational Intelligence Society Outstanding PhD Dissertation Award, and an awardee of the 2014/15 Early Career Award by the Research Grants Council of Hong Kong.
For more information, please visit http://www.dcs.shef.ac.uk/~haiping
-The Department
The Department of Computer Science at the University of Sheffield was established in 1982 and has since attained an international reputation for its research and teaching. In the recent Research Excellence Framework (REF2014), 45% of the research in the department was recognised as internationally excellent in terms of originality, significance and rigour, and another 47% as internationally world leading. These results place the department among the top 5 UK Computer Science departments for research excellence.