or
Continue with FacebookLooking to list your PhD opportunities? Log in here.
This project is no longer listed on FindAPhD.com and may not be available.
Click here to search FindAPhD.com for PhD studentship opportunities
Dr N Poh
No more applications being accepted
About the Project
Applications are invited for a 3-year Ph.D. project hosted in the Department of Computing, University of Surrey, UK.
Supervisor: Dr Norman Poh
Co-supervisor: Dr David Windridge
Due to technological advances, addressing the growth in the size of data sets used by science, medicine and industry has become an increasingly central concern. In this PhD, the candidate will work towards advancing machine-learning and data-mining algorithms for processing big data by addressing some or all of the following issues: handling of sampling bias and structural noise, handling of under-sampled and miss-labelled data; handling of covariates or confounding factors; exploitation of temporal logics; and finally, efficient retrieval of related data queries. The techniques developed will be applied to a number of application domains, including healthcare records, bioinformatics, business data, and data collected from ubiquitous sensing.
The candidate will contribute towards building a critical mass of strategic competency in healthcare analytics within the Computing department, and will work in a multidisciplinary team involving clinicians and IT engineers.
Required experience and qualifications:
- Masters-level degree in computer science, mathematics, statistics, or machine Learning; or equivalent research/industrial experience in data analysis
- A good command of English, as well as open-mindedness and the will to collaborate within a team
Additional desirable features:
- A record of peer-reviewed publication
- Evidence of system implementation
- Knowledge of statistical packages and high-level programming such as Matlab, R, and Python
- Knowledge of databases and SQL
Supervisor: Dr Norman Poh
Co-supervisor: Dr David Windridge
Due to technological advances, addressing the growth in the size of data sets used by science, medicine and industry has become an increasingly central concern. In this PhD, the candidate will work towards advancing machine-learning and data-mining algorithms for processing big data by addressing some or all of the following issues: handling of sampling bias and structural noise, handling of under-sampled and miss-labelled data; handling of covariates or confounding factors; exploitation of temporal logics; and finally, efficient retrieval of related data queries. The techniques developed will be applied to a number of application domains, including healthcare records, bioinformatics, business data, and data collected from ubiquitous sensing.
The candidate will contribute towards building a critical mass of strategic competency in healthcare analytics within the Computing department, and will work in a multidisciplinary team involving clinicians and IT engineers.
Required experience and qualifications:
- Masters-level degree in computer science, mathematics, statistics, or machine Learning; or equivalent research/industrial experience in data analysis
- A good command of English, as well as open-mindedness and the will to collaborate within a team
Additional desirable features:
- A record of peer-reviewed publication
- Evidence of system implementation
- Knowledge of statistical packages and high-level programming such as Matlab, R, and Python
- Knowledge of databases and SQL
Funding Notes
The candidate will receive Home or EU fees (currently £3,828) and a tax-free maintenance grant per annum (currently £11,400). Non-EU students are expected to be in a position to cover the difference between the Home and Overseas Fees (currently £14,400). The studentship should be taken up no later than 1 July 2013. For full details and informal discussions, please refer to Dr Norman Poh’s website: http://personal.ee.surrey.ac.uk/Personal/Norman.Poh and click the vacancy tab.
References
To apply, please email Maggie.Burton@surrey.ac.uk with a CV, and relevant supporting materials such as transcripts, research reports, and publications. Candidates with no previous research experience may be asked to sit a short written examination.
Shortlisted candidates will then be asked to apply formally through the link:
http://www.surrey.ac.uk/postgraduate/courses/computing/computing-phd/apply. Applications will be continually received until the position is filled.
Shortlisted candidates will then be asked to apply formally through the link:
http://www.surrey.ac.uk/postgraduate/courses/computing/computing-phd/apply. Applications will be continually received until the position is filled.
Find a scholarship to fund your dream Masters
Sign in to view and filter all scholarship opportunities
or
Continue with Facebook