PhD Studentship in “An Intelligent Data Cleaning Tool for Big Data”

University of Derby

Department of Electronic, Mathematics and Computing

One funded full time traditional route PhD studentship is available as part of the University’s wider investment for the next Research Assessment Framework (REF). Building upon its successes in REF 2014, the Department of Electronic, Mathematics and Computing aims to deliver a 3* performance equivalent to internationally excellent level in the next round of REF assessment (expected in 2021). The studentship covers tuition fee to the UK home/EU level and provide a tax-free stipend of £14,777 pa for 3 years subject to satisfactory progress. The start date is January 2019 or the next available intake.

Qualification type:



Derby, UK

Funding amount:

£14,777 stipend pa + UK home tuition fees


Full Time


23 September 2018


w/c 8 October 2018

Start date:

January 2019

Data cleaning is considered as one of main challenges in the era of Big Data. Data cleaning is one of the key steps in “Data creation, deposit and re-use by discipline”. It is also the essential pre-processing step for “Research data analytics”. This proposal aims to build a data cleaning tool for research data by facilitating all aspects of data cleaning, such as error detection methods and data repairing algorithms. The initial case study will focus on geoscience research data. A tool built for cleaning data will have the followings objectives: 1) Propose the suggestions on the potential errors; 2) Propose the possible corrections; and 3) Compatible for incorporation of high performance/throughput computation of data cleaning method using a workflow management system for distributed data placement and the variable sliding window technique for data screening from the perspective of big data, in terms of volume, velocity and variety.

You would work within a multi-disciplinary team in the Department of Electronics, Computing and Mathematics at the University of Derby with expertise in both the mathematics and computing aspects of this challenge.

Teaching responsibilities

Prospective candidates will also have a post graduate teaching assistant (PGTA) status within the College. On average over a calendar year a PGTA should be prepared to spend a maximum of 250 hours on teaching-related duties. These duties include teaching contact, preparation and any assessment. In practice during semesters, which extend for about 24 teaching weeks per year, the PGTA may expect on average to be engaged in teaching-related duties for about 10 hours per week. This teaching-related work will not exceed 20 hours in any single week. In addition to days in which no engagement is expected, there should be at least a further 16 weeks each calendar year when the PGTA has no teaching duties. There is no additional remuneration in respect of these teaching duties. In addition to their teaching duties which automatically contribute towards their teaching development, the successful candidates are also expected to commit a minimum of further 17 hours per week over 45 weeks each year to their programme of personal research.

Entry Requirements

Previous research experience is required, either at Masters level or as strong component of independent project work at Bachelor's level. Prior experience with Big Data would be an advantage but is not essential. We welcome applications both from candidates with a first degree in a Mathematics-related subject, with a strong interest in computing and from candidates with a first degree in a computing-related subject with an interest in working in the Big Data science.

How to apply:

In order to apply, please see the University website at In addition to the documents requested on the website, please also include with your application a Curriculum Vitae and a covering letter. Completed applications should be submitted by email to, quoting reference E&T_DataCleaning_PGTA_0918 in the subject line.

For further information and informal discussions on possible research topics please contact Professor Yong Xue (, Please note that applications sent directly to this email address will not be accepted. If you have not been invited for interview by the interview date, please assume that on this occasion your application has not been successful.

Studentships are available to UK/EU and International applicants. If your application is successful and you are assessed as Overseas for fees purposes, you will need to pay the difference between the Home/EU fees and the Overseas fees.