PhD in Big data privacy - methods that provide privacy guarantees when big data is used for machine learning and data mining.
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ORGANISATION NAMEMaynooth University
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ORGANISATION COUNTRYIreland
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FUNDING TYPEFunding
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DEADLINE DATE04/01/2019
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RESEARCH FIELDProfessions and applied sciences
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CAREER STAGEFirst Stage Researcher (R1) (Up to the point of PhD)
Outline
The PhD student will conduct research within the area of data privacy for big data. The successful applicant will work on methods that provide privacy guarantees when big data is used for machine learning and data mining. The student is expected to be excellent in computer science (including programming) and mathematics. This PhD position is funded by Prof. Torra's initial start-up funds. Supervisor’s web page: http://www.mdai.cat/vtorra/
All applicants must have:
• Relevant 2:1 degree (or higher) in Mathematics, Engineering, Physics, Computer Science, Statistics, Machine Learning, Data Science, or similar qualification
• Ability to code in one or more of Matlab, C, R or Python
• Strong linear algebra and calculus skills
• Excellent written and verbal communication and presentation skills in English
The studentships are for 48 months and include a tax free stipend of €18,500 p.a. and the payment of academic fees up to a maximum of €5,500 per annum, as well as a computer and travel allowance.
Application Procedure: send a curriculum vitae and a cover letter to hamilton@mu.ie with PHD X in the subject line indicating the desired PhD project. Candidates are allowed to express interest in multiple PhD proposals
Interview: to be advised. Appointment April/May 2019.
Closing date for applications: 1st March 2019.
What is funded
The studentships are for 48 months and include a tax free stipend of €18,500 p.a. and the payment of academic fees up to a maximum of €5,500 per annum, as well as a computer and travel allowance.
Duration
The studentships are for 48 months.
Eligibility
All applicants must have:
• Relevant 2:1 degree (or higher) in Mathematics, Engineering, Physics, Computer Science, Statistics, Machine Learning, Data Science, or similar qualification
• Ability to code in one or more of Matlab, C, R or Python
• Strong linear algebra and calculus skills
• Excellent written and verbal communication and presentation skills in English