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Research Studentships and Fees-only Bursaries

Doctoral Studentships in The Faculty of Arts, Environment and Technology

About the Programme
The Faculty of Arts, Environment and Technology offers a unique environment for integrating research across a range of areas covering culture, creativity, design, sustainability and digital domains. This environment provides opportunities for developing exciting multi-disciplinary and inter-disciplinary research projects.

The Faculty is offering 6 fully funded Doctoral Studentships for an October 2016 entry. The studentships will be for a maximum of 4 years duration. Each studentship has an annual stipend of £14,296. The additional Doctoral tuition fees will be waived. The studentships are available in the following areas.

1. Doctoral Studentship in Computer Security

The Cybercrime and Security Innovation Centre (CSI Centre) aims to improve and incorporate an evidence-based approach into the frontline policing of digital forensics and cybercrime investigations, and to advance human factors of computer security and forensics mechanisms and practice. The Centre acts as a collaborative hub for high quality research, with a collegial, supportive and cooperative research-intensive group, aimed at high-impact outputs. The CSI Centre has a close working relationship with West Yorkshire Police force; working directly with the Digital Forensics Unit (DFU) and Cyber Crime Team (CCT) to investigate and improve the way cybercrime and digital evidence is processed. Our diverse and complementary academic team includes those that specialise in computer security, digital forensics, privacy and surveillance, artificial intelligence and analytics, and criminology. We have a portfolio of research projects (leading £1.5m in recent research funding), and benefit from great links with many partnering organisations and associates. 

We welcome research proposals in any area of computer security (including systems security, cybercrime, and digital forensics). In particular, we are interested in applicants interested in working to propose, design, develop and evaluate novel technical solutions. For example (but by no means exclusively): by extending the Android/Linux platform with new usable security and privacy features; new methods for digital forensics analysis or support for police officers; or new methods for automating or reasoning about security audits/vulnerability assessments/hacking.

The successful candidate should have an Honours Degree at 2.1 or above, or equivalent, in an ICT-related degree, will have a strong interest in security, and will have experience in software development, preferably with programming experience using Java, C and/or C++. 

This position involves some teaching in the areas of digital security and forensics, computer science, and/or computing.

The closing date for Studentship applications is midnight 28 August 2016 for entry in October 2016.

Candidates are encouraged to contact Dr Z. Cliffe Schreuders to informally discuss their application or research ideas.

2. Doctoral Studentship in Ambient Assisted Living

An important area of research within the School of Computing, Creative Technologies and Engineering at Leeds Beckett University is ambient assisted living (AAL). The goal in AAL is to develop systems and tools to support independent living. The school wishes to further develop its existing strengths in AAL by attracting outstanding doctoral candidates that are willing to work on state-of-the-art research projects, making an original and novel contribution to the field. 
Expressions of interest in the following research areas will be considered:
1. Sensor-based human behaviour understanding to assess performance
2. Adaptive task sequencing to support people with cognitive problems
3. Serious games and action recognition to support rehabilitation
4. Real-time fault detection and system recovery for a smart home sensor network.
The research will employ modern pattern recognition methods to identify patterns in complex data and information fusion methods to combine information from multiple sensor modalities.
Your background
Good first degree in computer science, software engineering, computer engineering or other numerate discipline e.g. electronic engineering with a significant computer programming content or MSc in computer science / artificial intelligence, …
Good scientific programming skills (C++, C#, Python, …)
Some familiarity with Artificial Intelligence specifically machine learning techniques, computational modelling techniques…

The closing date for Studentship applications is midnight 28 August 2016 for entry in October 2016.

Candidates are encouraged to contact Professor Dorothy Monekosso to informally discuss their potential application or research ideas.

3. Doctoral Studentship in Machine Intelligence based optimisation of Flying Ad Hoc Networks for disaster management applications

This project will investigate, select and apply appropriate machine intelligence (particularly nature-inspired paradigms) and multi-criteria evaluation techniques for the optimisation of Flying Ad Hoc Networks (FANETS) in disaster scenarios, within a simulated environment. 

A key scientific challenge will be to achieve high level of optimisation performance based on multiple objectives, in such a dynamic environment.

This research project will build on an existing collaborative project (with University of Seville, Spain) which involves the use of artificial intelligence methods for the efficient and dynamic adjustment of the location of drones for natural disaster management and emergency purposes, using simulation scenarios. 

The candidate will normally be expected to have a computer science or electronic engineering educational background with a particular interest and competency in machine learning/optimisation algorithms and a good programming experience. 

Experience in network simulation, Matlab and/or Python will be particularly desirable as will be the aptitude to work effectively as part of a collaborative research project.

Project supervisor: Professor Hissam Tawfik

The closing date for Studentship applications is midnight 14 August 2016 for entry in October 20164.

Candidates are encouraged to contact Professor Hissam Tawfik to informally discuss their potential application or research ideas.

4. Doctoral Studentship in Smart Online Monitoring of Nuclear Power Plants

Both existing and new design Nuclear Power Plants (NPP) strive to improve safety, maintain availability and reduce the cost of operation and maintenance. However, plant life extensions and power updates push the demand for the new tools of diagnosing the health of NPP.

A PhD student will be required to build a reliable monitoring tool used in the control room operator desk setting of nuclear plants. The aim is to employ computational intelligence methods to monitor accident progression, predict the onset and evolution of an accident, and support operators in their decision-making process using available information from the plant’s online monitoring database. The tool will improve safety, maintain plant availability and reduce accident handling costs in nuclear power plants.

The closing date for Studentship applications is midnight 28 August 2016 for entry in October 2016.

Candidates are encouraged to contact Professor Jiamei Deng to informally discuss their potential application or research ideas.


5.  Doctoral Studentship in Speech and Language Technology.

Speech and Language Technology (SLT) plays an increasing role in everyday life, to such an extent that many people are now familiar with and routinely use automated translation engines, speech recognition systems (telephone agents, smart phone transcribers, in-car voice control), or tools to create documents by voice. Most rail travellers are also familiar with speech synthesisers of greater or lesser capability.

Whilst progress and capability development has been impressive over the last 10 years in particular, such tools still have some way to go before their performance reaches that of the communication skills routinely exercised by people. Leeds Beckett University is therefore initiating research into why and how SLT fails to deliver accuracy and quality on a par with human performance, with the aim of understanding the causes of inaccuracy and exploring generic ways to overcome them. This research will inform not only the SLT area but also AI and computational linguistics.

The successful candidate will have an awareness of the state of the art in SLT, a good grasp of linguistics, and computational ability ideally with software development skills. Whilst initially focusing on English, the project is likely to expand to encompass other mainstream European languages and some awareness of these languages will be of benefit.

The primary contribution will be in devising tools, techniques and ideas to assist in the assessment of automated SLT processes such as transcription or speech synthesis. This assessment will be used to create a classification of error cases in which the system does not match human performance, and analysis of novel ways automatically to reduce the instance of such errors. Pre-processing and post-processing tools will be developed in order to maximise quality as generically as possible in order to make a broad contribution to the body of knowledge rather than being tied to any particular system. The project will also seek to develop benchmarking tools in order to assess competing technologies and approaches in controlled conditions.

Raw material for analysis may include real-time respoken subtitles intended for deaf and hard-of-hearing TV viewers, output from speech synthesisers, and speaker-independent transcripts of graded test pieces. The successful candidate will have excellent skills in spoken and written English, a methodical and ordered approach, and the ability to formulate and test hypotheses for ways in which overall accuracy and reliability can be improved in the general case.

The closing date for Studentship applications is midnight 28 August 2016 for entry in October 2016.

Candidates are encouraged to contact Professor Andrew Lambourne 
to informally discuss their potential application or research ideas.


Timeline and How to Apply
A PhD application pack is available here. Please see individual Themes for closing dates.

The Faculty is always happy to discuss other innovative proposals for research on a case by case basis.