Apply for a funded PhD position

Details

Start date: April 2023

Deadline for application: 8th February 2023

Interviews: from 15th February 2023

Description

Join us in the School of Computing and Communications for a PhD in Computer Science! The School is growing and we offer 8 studentships available for UK students, for start in April 2023. The studentships are fully funded for 3 years including a tax-free stipend (£17,668 in year 1) and tuition fees.

We provide a diverse, inclusive and stimulating research environment in the School of Computing and Communications. As a doctoral student, you can focus your computer science research in any area covered by our research groups and interdisciplinary research institutes. Supervision will be provided from world-leading and internationally excellent academic staff, who will develop your knowledge and skills and share the professional networks they have built through their own cutting-edge research. You will have access to outstanding research facilities and to a wide range of training opportunities for your personal and professional development. In the School, you will become part of the lifeblood of our community of over 200 research staff and students, housed in the iconic InfoLab21 building on the University’s main campus, located in beautiful countryside just outside the city of Lancaster.

About You

Applicants must have a strong motivation and commitment to all aspects of academic activity. We expect successful candidates to contribute as Graduate Teaching Assistants (GTA) to teaching-related activity in core computer science courses for an average of between 4 and 6 hours per week over the course their studentship, for which there will be a separate payment. As the studentships are provided for a PhD through full-time study, successful applicants will be expected not to take any employment other than the GTA role during their PhD studies.

Academic requirements

The studentships are available only for applicants who are eligible for Home Fee status. The minimum entry requirement for a PhD is a 2:1 honours degree in Computer Science or other relevant discipline. Excellent written and oral communication in English is a prerequisite.

Application Process and Next Steps

Applications must be submitted via Lancaster University’s online application system, and include a CV, academic transcript, personal statement, research proposal and at least one academic reference.

You can apply with a specific research project proposal that you have developed in consultation with a prospective supervisor in the School, or with a general research proposal that discusses your interest in a selected research area of the School with reference to any of our recently published work. Your personal statement should motivate your interest in a PhD in the School and reflect on what you can bring to the School, including in support of teaching as a GTA.

Contact Information

Prospective applicants are welcome to contact the School’s Director of Postgraduate Studies, Professor Hans Gellersen, for an informal discussion regarding their interest.

Details

Start Date: October 2023, with the flexibility to start in January 2024 if necessary

Deadline for applications: Open-ended: please apply as soon as possible

Interview Date: To be confirmed

Academic Requirements: First-class or 2.1 (Hons) degree, or Master's degree (or equivalent) in an appropriate subject

Description

Two fully funded PhD studentships for UK applicants, including fees and stipend, are available for candidates to join the BBC partnership 'AI4ME' in the School of Computing & Communications at Lancaster University.

AI4ME is an exciting five-year EPSRC & BBC-funded Prosperity Partnership that is addressing the key challenges involved in creating and delivering personalised content at scale. AI4ME brings together the BBC, Lancaster University and the University of Surrey to design entirely new types of media experiences that can adapt to individual preferences, accessibility requirements, devices, and location. This is a unique opportunity for students to join a major new research partnership and take advantage of this vibrant collaborative research environment.

AI4ME builds upon the rapid changes underway within the industry in how media experiences are produced and delivered, from television and films to video games. In television and broadcast media, the prevalence of Internet-based delivery supports the independent transport of different parts of a stream – including audio, video, and additional media experience components – to be composed together at the point of playback. This paradigm is enabling new forms of hyper-personalised and immersive storytelling and represents both opportunities and new challenges in the network delivery of these experiences.

We are looking for two PhD candidates to be part of our exciting journey in building the world’s first hyper-adaptive end-to-end delivery infrastructure to deliver personalised object-based media on an unprecedented scale. This will require research in computer networking and distributed systems.

The following represent possible areas that could form the basis of your PhD:

• Novel Self-Adaptive Distributed Systems Paradigms: new approaches to building distributed systems, in which self-adaptive behaviours are at the core of the system’s capability.
• Distributed Reinforcement Learning: developing new techniques which scale well for state-of-the-art real-world stream processing systems.
• Orchestration Methods, Models, and Languages: how orchestration models or languages can be used within a highly adaptive deployment infrastructure to provide services that meet specific delivery criteria.

About You

You will have a 1st or 2:1 (Hons) degree in Computer Science (or related field), or a Master's (or equivalent) in a relevant engineering or scientific discipline or equivalent specialist experience. You need to have a genuine interest, and ideally experience, in computer networking or distributed systems and should be able to demonstrate strong computer programming skills. Evidence of research skills, for example, through a significant Bachelor's / Master's project involving experimental research, appropriate use of the literature and a formal dissertation-style report will be considered a plus.

Funding

These PhD studentships are open to UK students and cover university tuition fees for 4 years and a tax-free maintenance grant (stipend) of £17668k per annum. The studentships also include funding to support travel costs to present research at national and international conferences.

Application Process and Next Steps

General enquiries are welcomed by Professor Nicholas Race by email (networkedsystems@lancaster.ac.uk)

Otherwise, you may apply directly: Applying for postgraduate study mentioning the “AI4ME PhD studentship”.

Details

Start Date: October 2023, with flexibility to start in January 2024 if necessary

Deadline for applications: Open-ended: please apply as soon as possible

Interview Date: TBC

Academic Requirements: First-class or 2.1 (Hons) degree, or Master's degree (or equivalent) in an appropriate subject.

Description

A fully funded PhD iCASE studentship for UK applicants, including fees and enhanced stipend is available in the School of Computing & Communications at Lancaster University. The studentship is supported by British Telecom (BT) and will be jointly supervised by Lancaster University and BT.

Object-Based Media (OBM) allows the content of TV programmes and other media experiences to be customisable for each individual viewer. By decomposing and delivering the media content as multiple and individually separate objects, the viewer can effectively act as their own broadcast director and determine their own viewing experience.

OBM has been the subject of research by BT, the BBC and others for several years and, with personalisation being seen as the primary driver of growth in the $2.3Tn global media industry (PWC, 2020), broadcasters and content service providers are beginning to adopt object-based approaches as a means of differentiating mainstream TV production. However, the OBM community also recognises that significant challenges exist in establishing end-to-end workflows for object-based experiences, from capture to production to delivery at scale.

While there are well-established standards and techniques for measuring the perceptual quality of individual audio-visual components, there is limited work studying methods for measuring the perceived quality of object-based experiences across different user contexts (including devices, user preferences/interactions, connectivity and user environment). Hence, there is a need to combine established techniques with new studies on the perceptual impact of new types of rendering artefact which arise from the personalised assembly of different objects (e.g. combining different display resolutions and sound sources).

What will the PhD involve?

• Background research into the state of the art in the perceptual quality measurement of audio-visual media
• Background research into delivery platforms for OBM and the challenges of combining platforms for cost-effective delivery
• Experimental identification of the parameters of an OBM presentation which affect perceptual quality
• Development and evaluation of new perceptual quality measures for OBM
• Development and evaluation of tools which can automatically measure the quality of an OBM presentation and identify/predict poor customer experience. These could potentially be extended to provide a feedback loop to the OBM delivery system to better balance cost and quality

About You

You will have a 1st or 2:1 (Hons) degree in Computer Science (or related field), or a Master's (or equivalent) in a relevant engineering or scientific discipline or equivalent specialist experience. You need to have a genuine interest, and ideally experience, in computer networking – particularly around the topics of video distribution and quality of experience (QoE). You should also be able to demonstrate strong computer programming skills. Evidence of research skills, for example, through a significant Bachelor's / Master's project involving experimental research, appropriate use of the literature and a formal dissertation-style report will be considered a plus.

Funding

This PhD studentship is open to UK students and covers university tuition fees for 4 years and a tax-free maintenance grant (stipend) of over £20k per annum. The studentship also includes funding to support travel costs to present your research at national and international conferences.

Application Process and Next Steps

General enquiries are welcomed by Professor Nicholas Race by email (networkedsystems@lancaster.ac.uk)

Otherwise, you may apply directly: Applying for postgraduate study mentioning the “BT OBM iCASE PhD studentship”.

Details

Deadline for applications: 31st March 2023

Start date: 1st August 2023

Interview Date: TBC

Academic Requirements: Candidates should have a 1^st class degree (or equivalent) in computer science or a closely related discipline with an interest in distributed systems, machine learning, and code generation. Strong programming skills are essential. Experience in system orchestration, component-based development, and applied machine learning are useful but not required.

Description

Our existing research has developed the concept of emergent software systems which learn ho best to construct themselves from a pool of potential behaviour. We have also undertaken initial research into how genetic improvement processes can automatically synthesis improved potential building blocks for injection into a running system. This PhD studentship is attached to a new research project in which we are taking our live genetic improvement approach to the next level, by incorporating novel methods in phylogenetics and meta-population theory. This PhD itself will examine the potential for human interaction and input into genetic improvement processes which operate continuously on the source code of live software.

This human interaction will take at least two forms: (i) high-level guidance of phylogenetic and meta-population processes based on novel visualisations; and (ii) direct intervention-based guidance using fuzzy templates of code structures that an experienced engineer believes may represent a search space area worth exploring.

In high-level guidance, you will develop novel visual representations of phylogenetics that allow humans to interact with an improvement process and to bias the direction of the genetic algorithm; this can be used to explore parts of the population which the human supervisor sees as more promising or diverse than others.

In direct intervention, we will develop an interface to express fuzzy code templates, such as a nested for-loop, and a protocol for how these templates will interact with existing code (and with ongoing mutations and crossovers). This will enable a genetic search process to move much larger distances in the search space to find potentially more promising areas to examine. By relying on experienced engineers to identify multi-line logic which may be helpful, we can examine how direct human guidance can effectively jump through neutral areas of program space to higher-value solutions.

As we gain more experience from human-driven insertion of complex code templates, we will also explore the use of machine-learning to support automated advice to the user when particular template features that they suggest may be of low utility in aiding the GI process with respect to the current population features. This may further drive a positive feedback relationship with a user, in provoking users to consider more unusual templates that have been under-explored. Output of this work will be published at leading systems conferences such as ICSE, GECCO, and ACSOS, among other suitable venues.

Application Process

Please send the following to Dr Barry Porter at b.f.porter@lancaster.ac.uk:

• A CV (2 pages maximum)
• Cover letter, explaining your interest in this PhD and your background
• Undergraduate degree transcripts

Contact Us

We very much welcome informal queries about this opportunity, which should be directed to Dr Barry Porter (b.f.porter@lancaster.ac.uk).

Details

Start Date: October 2023, with flexability to start in January 2024 if necessary

Deadline for applications: 18th August 2023

Interview Date: w/c 28th August 2023

Academic Requirements: First-class or 2.1 (Hons) degree, or Master's degree (or equivalent) in Computer Science, Statistics, or a related field.

Description

We invite applications from highly motivated PhD candidates with interest in cyber security, statistics, and cyber physical systems. The studentship is available from October 2023 or later and it is fully funded for at least 3 years only for applicants who are eligible for Home Fee status. Excellent written and oral communication in English is a prerequisite.

This studentship is attached to an EPSRC funded project investigating how to mitigate cyber physical systems revealing information to adversaries observing them. Data privacy techniques are often necessary, but insufficient in protecting against this information loss. So, this PhD would investigate techniques to mitigate context privacy threats.

The studentship will focus on specific advances in developing novel techniques to provide context privacy, this could include:

• Quantifying the amount of information a system reveals to an adversary observing it,
• Developing context privacy techniques for arbitrary systems and demonstrating their effectiveness,
• Translating techniques for arbitrary systems to real-world systems, and
• Testing these techniques in practice.

About you

You must have a 2:1 BSc Honours or Master’s degree in Computer Science, Statistics, or a related field. This research melds theoretical foundations with practical experimentation, so strong programming skills are recommended. Any experience with cyber security, cyber physical systems, embedded systems, information theory, or differential privacy is a plus.

Applicants must have a strong motivation and commitment to all aspects of academic activity. We expect successful candidates to contribute as a Graduate Teaching Assistant (GTA) to teaching-related activity in core computer science courses for an average of between 4 and 6 hours per week over the course their studentship, for which there will be separate payment.

Funding

£18622 tax-free stipend plus tuition fees.

Application Process

You will be supervised and mentored by Dr Matthew Bradbury. If you consider applying, you should first contact him informally for discussion of your interest.

You may apply online, following the University’s guidance regarding the required documentation. Apply for “2023 Entry” even if you are interested in a later start, to ensure that we receive your application without delay. Select “PhD Computer Science - Full Time” and name Matthew Bradbury as your proposed supervisor.

Contact information

Dr Matthew Bradbury

School of Computing and Communications, Lancaster University

m.s.bradbury@lancaster.ac.uk