A fully-funded PhD studentship: UWE Bristol Computer Science Research Centre and Airbus
An opportunity to apply for a fully funded 3 year PhD in the area of Big Data Analytics and Machine Learning within the Computer Science Research Centre. The studentship will be jointly funded by UWE Bristol and Airbus. Ref: 1920-OCT-FET07.
Studentship start date: 1 April 2020
Closing date for applications: 15th February 2020
Interview date: TBC
About the studentship
Computer Science Research Centre (CSRC) of the University of the West of England (UWE) in partnership with Airbus, are pleased to offer a PhD studentship: In the current era, new aircraft are being constructed with a variety of new materials to improve efficiency but, perhaps more importantly, they are also being fitted with a range of data collection capabilities and measurement tools to provide greater feedback. The possibility for organisations and departments to maintain, repair or replace components before they fail promises to improve safety, reliability, and reduce costs. Due the wealth of data in the Aerospace industry there is a drive for increased automation, particularly to organise and analyse this data to help in the decision-making. Therefore, there is a growing need to build smart theoretical and practical solutions, which can automate most (if not all) of the data analytics in order to quickly and intelligently predict the need of repair or replace aircraft systems components.
This PhD research will aim to investigate intelligent methods to automatically identify predictive and preventive maintenance trends using various real time and historical datasets collected from aircraft systems. This will be achieved by the application of artificial intelligence (AI), knowledge modelling and big data analytics techniques. It is expected that this will be achieved by research conducted in terms of automation of:
- identification of relevant data sources
- development of a domain knowledgebase of identified data sources
- data cleansing and format correction suggestions for related data files
- identification of the types of analytics possible on the available/selected parameters and considering both past incidents and future probabilities
- and execution of analytic queries/algorithms on the selected parameters and display trends in both graphical and textual formats, where applicable.
University of the West of England (UWE Bristol): The research at the Computer Science Research Centre (CSRC) addresses a wide range of topics relating the implementation in industry of novel and emerging technologies e.g. Data science, IoT and Big Data Analytics, artificial intelligence, etc.
Airbus: The project will be carried out in close collaboration with the Airbus’s UK Data Analytics Plateau team (Filton, Bristol site).This is a multi-functional team that aims to bring value through data analytics across all UK departments. This includes Aircraft Operability and Airworthiness, Flight and Systems Test, Aircraft Systems & Structures, Landing Gear, and Flight Physics.
For an informal discussion about the studentship, please contact Dr Kamran Munir Kamran2.Munir@uwe.ac.uk .
The studentship is for a period of three years, subject to satisfactory progress, and includes a tax-exempt stipend which is currently £15,009 per annum. In addition, full-time tuition fees will be covered for up to three years at Home / EU rates.
Applicants must have a good honours degree (2:1 or equivalent) in Computer Science or a closely related discipline, with a research interest in the areas of data analytics and machine learning.
Full funding is available for UK/EU applicants. Applications from outside UK/EU will be considered if the student is willing to cover/self-fund the difference between UK/EU and international fee, as specified here.
All applicants must show proof of a recognised English Language Qualification that is required to be eligible.
Moreover, applicants need have Computer Science and Mathematics background with experience in:
- Programming using Java or Python
- Knowledge of database system, SQL/NOSQL and data analytics
- Familiarity with data cleansing and wrangling processes
- Knowledge of Big Data, Machine Learning, Artificial intelligence, Neural Network and Deep Learning
- Cloud Computing - general understanding of how to architect digital solutions that efficiently exploit cloud computing.
- Knowledge of time-series sampled data analysis and discrete time event analysis
How to apply
Please submit your application online. When prompted, use the reference number 1920-OCT-FET07.
Documentation: you will need to upload your research proposal, all your degree certificates and transcripts and proof of . English language qualification as attachments to your application, so please have these available when you complete the application form.
Research Proposal: please explain, in no more than 500 words, how your skillset and experience could contribute to this proposed PhD project.
Referees: you will need to provide details of two referees as part of your application. At least one referee must be an academic referee from the institution that conferred your highest degree. Please ensure that your nominated referees are willing and able to provide references before you submit your application.
The closing date for applications is 15th February 2020.
Interviews will take place within four weeks after the application deadline. If you have not heard from us by this date, we thank you for your application but on this occasion you have not been successful.