Apply for a funded PhD position

Details

Start Date: September 2022/October 2022 onwards.

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 Masters degree (or equivalent) in an appropriate subject

Description

Two fully funded PhD studentships 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 new five-year EPSRC & BBC-funded Prosperity Partnership that will address the key challenges involved in creating and delivering personalised content at scale. AI4ME brings together the BBC, Lancaster University and 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 Masters (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 Bachelors/Masters 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 both UK & International/EU students and cover university tuition fees for 3.5 years, a tax-free maintenance grant of up to £15,609 per annum and contribution to 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 (n.race@lancaster.ac.uk).

Otherwise, you may apply directly: http://www.lancaster.ac.uk/study/postgraduate/how-to-apply-for-postgraduate-study/ mentioning the “AI4ME PhD studentship”.

Details

Start Date: September 2022/October 2022 onwards.

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 Masters degree (or equivalent) in an appropriate subject

Description

A fully funded PhD iCASE studentship 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.

HTTP is used for unicast delivery of video services over the Internet. HTTP version 3 is currently in development in the IETF and should provide improvements over HTTP/2 and HTTP/1.1, with the primary difference for video streaming being the use of QUIC rather than TCP for data transport. QUIC provides developers with easier access to the congestion response than TCP, which creates a research challenge to jointly optimise the QUIC congestion response and the ABR algorithm to minimise latency and maximise quality of experience. BT already has a granted patent (A33513) on this subject, but there is large scope for further innovation.

The topics for the PhD could include:

• Accurately estimating network throughput when receiving content close to the live edge;
• Understanding viewers’ tolerance to quality variations (where perhaps small variations are more acceptable than we think) and understanding their tolerance to micro-stalls and changes in play-out speed;
• Developing a model of the variation of network throughput; and
• Using accurate network throughput estimates, the understanding of viewers’ tolerance to quality issues and the network model to derive solutions to the QUIC congestion response and the ABR algorithm optimisation problem, and to assess their performance.

About You

You will have a 1st or 2:1 (Hons) degree in Computer Science (or related field), or a Masters (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 Bachelors/Masters project involving experimental research, appropriate use of the literature and a formal dissertation-style report will be considered a plus.

Funding

This PhD studentship covers UK university tuition fees for 4 years, a tax-free enhanced maintenance grant of up to £18,609 per annum and contribution to travel costs to present your research at national and international conferences. Studentships are open to international students, from the EU and overseas, provided they can support the difference between home and overseas fees.

Application Process and Next Steps

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

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

Details

Start Date: October 2022

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

Interview Date: TBC

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

Description

A fully funded PhD studentship including fees and enhanced stipend is available for candidates to join the BT partnership ‘NG-CDI’ in the School of Computing & Communications at Lancaster University.

NG-CDI is an exciting five-year EPSRC & BT-funded Prosperity Partnership that is developing the next generation converged digital infrastructure for the UK, delivering a radically new data-driven architecture for the autonomous operation of future telecommunications infrastructure. The consortium brings together leading research groups from the Universities of Lancaster, Cambridge, Bristol and Surrey working alongside BT, one of the world's leading communications service providers. This is a unique opportunity for students to join a major research partnership and take advantage of this vibrant collaborative research environment.

The topics for the PhD could include:

• Orchestration of network services via an intent-based approach
• Use of P4 to support enhanced delivery of network services
• Exploration of a network-DevOps approach to service deployment with unikernels

About You

You will have a 1st or 2:1 (Hons) degree in Computer Science (or related field), or a Masters (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 and should be able to demonstrate strong computer programming skills. Evidence of research skills, for example, through a significant Bachelors/Masters project involving experimental research, appropriate use of the literature and a formal dissertation-style report will be considered a plus.

Funding

This PhD studentship covers UK university tuition fees for 3.5 years, a tax-free enhanced maintenance grant of up to £17,000 per annum and contribution to travel costs to present your research at national and international conferences. Studentships are open to international students, from the EU and overseas, provided they can support the difference between home and overseas fees.

Application Process and Next Steps

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

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

Details

Start Date: September/ October 2022 onwards

Deadline for applications: TBC

Interview Date: TBC

Academic Requirements: First-class or 2.1 (Hons) degree, or Masters degree (or equivalent) in the topic appropriate subject eg. Computer science, systems security, Machine Learning, etc.

Description

A wide variety of autonomous systems (in domains such as critical infrastructure, technology, and defence) are either presently or are expected to incorporate Machine Learning (ML) as a core technology to deliver their functionality. Due to the increased criticality of ML within autonomous systems, it is important that such ML models are secured against a wide variety of adversarial cyber attacks attempting to extract the ML model characteristics and data leakage. However, understanding and defending ML-enabled autonomous systems is challenging giving the plethora of attack and deployment scenarios, as well as determining appropriate countermeasures required.

For this PhD position, we seek candidates interested in developing novel theoretical foundations and practical technologies towards understanding and securing ML-enabled autonomous systems against cyber attacks. We are interested in the development and analysis of new and existing adversarial cyber attacks against ML within autonomous systems, and proposed new defences in order to enhance system privacy and confidentiality towards achieving trustworthy ML systems.

The appointed candidate will reside in the Systems Security Group (SSG) and Experimental Systems Laboratory(EDS Lab) and will interact closely with the Trustworthy Autonomous Systems Node in Security (TAS-S) project. Professor Neeraj Suri and Dr Peter Garraghan will co-supervise, please contact Peter with informal enquiries. Due to restrictions on the post we are only able to accept applicants with an existing right to work in the UK.

Further details and application process

• Each PhD positions is for a three and a half years duration. Tuition fees are covered (for EU/UK citizens) along with a tax-free stipend for the duration of the PhD.
• Candidates should submit an application following the instructions provided on our Applying for postgraduate study webpage.

Please note if English is not your first language you will be required to provide evidence of your proficiency in English. For more information please visit our entry requirements webpage. We only need this evidence if we offer you the funded position. We don’t expect it as part of this application process.

Details

Start date: October 2021, or later

Deadline for application: Open-ended

Interview date: TBC

Academic requirements: Masters degree (or equivalent) in a relevant field.

Description

We invite applications from highly motivated PhD candidates with an interest in HCI technology and their foundations in human vision and movement. The studentships are fully funded for up to 4 years and open to students from anywhere in the world.

Eye movement and gaze are central to human interaction with the world. Our visual system not only enables us to see the world but also provides exquisite control of the movements we make in the world. The eyes are at the heart of this, never still, closely coupled with other parts of our body, and dynamically responding to motion in the world. In this project, we aim to harness the power of the eyes for human-computer interaction in 3D.

Our goal is to develop multimodal interfaces in which gaze is central and input from eye, head, hand and body movement combined smartly for natural and powerful interaction with devices around us, and in virtual, augmented and extended realities. This requires basic and creative research with broad scope for definition of PhD projects, for example, on:

• eye, head and body coordination and design principles for 3D user interfaces
• inference of attention and intent from continuous eye and body movements
• gaze input based on specific types of eye movement (smooth pursuit, vergence)
• combination of gaze, gestures and proxemics for touchless interaction in 3D worlds.

You must have a relevant Masters Degree (or equivalent) in Computer Science, HCI or related field. You need to have a genuine interest, and ideally experience, in human-centred computing, and should have relevant design, prototyping and programming skills. Any experience with VR/AR, Gaze/Gestures, or AI/ML techniques applicable to HCI is a plus.

The studentships are available in an ERC Advanced Grant project, and you will be part of a team with a strong commitment to collaboration, learning from each other, and mutual support.

You will be supervised and mentored by Professor Hans Gellersen. If you consider applying, you should first contact him informally for discussion of your interest (h.gellersen@lancaster.ac.uk).

Contact information

Professor Hans Gellersen

School of Computing and Communications, Lancaster University

Details

Closing Date: 2 May 2022

Start Date: October 2022

Interview Date: May 2022

Academic Requirements: First-class or 2.1 (Hons) degree, or Masters degree (or equivalent) in an appropriate subject, i.e., Computer Science, HCI, Design

Description

We invite applications from highly motivated PhD candidates with an interest in HCI and technologies for wellbeing. These studentships are fully funded for 3.5 years. One scholarship is for UK students, and one is for international students.

The importance of wellbeing for fulfilling and productive lives cannot be overstated, and mindfulness practices have shown great potential in this respect. However, there has been limited exploration of how mindfulness principles can be used to inform novel design of interactive systems to support more mindful everyday behaviours from eating and financial budgeting to smartphone use.

Each of these two studentships aims to explore, design, implement, and evaluate innovative technologies to support a specific everyday behaviour becoming more mindful, i.e., mindful eating, financial wellbeing, digital wellbeing.

Successful candidates will be part of a team engaged in award winning research, with a strong commitment to high quality interdisciplinary research, and to the academic development of young researchers. You will contribute to the School’s strong research agenda on HCI and digital health to meet the growing societal needed in this space. In addition, the School of Computing and Communications offers a highly inclusive and stimulating environment for career development, and you will be exposed to a range of further research training opportunities throughout these studentships.

We are seeking applicants from graduates with a good degree: First-class or 2.1 (Hons) in Computer Science or related field, or a Masters (or equivalent) in Computer Science, HCI, Design or related field. You must have the demonstrable potential for creative, high-quality PhD research. Strong programming skills are essential with experience of developing mobile apps, games, or wearable technologies. In addition, HCI research, design methods, and academic writing skills are desirable.

You will be supervised and mentored by Professor Corina Sas, who in 2021 has been shortlisted by the UK Times Higher Education for the Outstanding Research Supervisor of the year Award.

Contact information

Interested applicants are encouraged to contact Professor Corina Sas for an informal conversation on your interest.

Studentships funding

Each scholarship covers the tuition fee, and include tax-free stipends for 3.5 years of over £15K per year.

Details

Start Date: October 2022

Deadline for applications: TBC

Interview Date: May - August 2022

Academic Requirements: First-class or 2.1 (Hons) BSc degree, or MSc degree (or equivalent) in Computer Science.

Description

ICT now consumers 10% of global electricity usage, with AI technologies in particular rapidly growing in size and demand. Thus it is imperative that new state-of-the-art computing systems are designed capable of delivering Net-Zero ambitions. This requires thinking beyond only achieving greater software and hardware efficiency, and instead a significant rethink as to how AI and Deep Learning operates within computing infrastructure -- for individual computers and at datacenter scale.

The goal of this PhD project is to design the next generation of Net-zero AI computing infrastructure towards designing new software and hardware approaches enabling AI to dynamically adjust their performance and energy use at run-time. This may include, but not limited to: capturing the end-to-end lifecycle of AI energy, energy-aware Deep Learning training and compilation, and Net-zero AI datacenters. You will have to opportunity to work with cutting-edge system and AI technologies, state-of-the-art GPU hardware, and access to 150-machine datacenter for experimentation.

The Experimental Distributed Systems Labaratory (EDS Lab) is a leading UK research group in computer systems, with heavy emphasis on experimentation and working on real-world problems. Our group has a strong track record of industrial collaboration, with team members finding employment during or post PhD study with leading technology labs including Microsoft, Huawei, Alibaba, ARM and BT.

The successful candidate will have an BSc Hons (first-class or 2:1) or MSc in Computer Science and a capability or a strong interest in distributed systems, energy-efficiency, and Deep Learning systems. This research will entail a strong element of conducting experimentation, thus confidence within programming, design, and implementation of computing systems is strongly recommended.

Supervisors

This PhD will be supervised by Dr Peter Garraghan. Applicants are strongly encouraged to contact Dr Garraghan prior to submission

Details

Start Date: October 2021 onwards (Also with potential to start in Jan 22)

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

Interview Date: Rolling – to be Confirmed

Academic Requirements: First-class or 2.1 (hons) degree in computer science, Or Master degree (or Equivalent) in an appropriate subject, Demonstrable interest in cyber security

Description

Applications are invited for an iCASE funded PhD studentship on Quantitative and Qualitative Methods for Cyber Threat Intelligence. The research will seek to explore approaches to quantify and measure various aspects of cyber threat intelligence so that a robust approach to threat comparison and exploration can be made.

There is a considerable number of CTI solutions on the market and there has been a significant growth in the adoption of CTI approaches. However, the current approaches largely focus on low level Indicators of Compromise. This project will explore and develop quantitative and qualitative approaches to CTI based on sound scientific methodologies. The aim is to increase the maturity of CTI such that the Tools Tactics and Procedures of threat actors (new or existing) can be identified, and that Threat actors may be tacked across different identities. This project will involve time embedded with industrial research partners

The objectives of the research are to develop a comprehensive understanding of the relevant literature and institutional background for cyber threat intelligence; to produce a systematic literature review, analysis of cyber threat intelligence approaches, understanding applicable quantitative and qualitative methods.

Entry Requirements

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

Funding

This PhD studentships cover UK university tuition fees for 3.5 years, a suitable tax-free maintenance grant and contribution to travel costs to present your research at national and international conferences. Studentships are open to international students, from the EU and overseas, provided they can support the difference between home and overseas fees.

Application Process and Next Steps

General enquiries are welcomed by Dr Daniel Prince by email (d.prince@lancaster.ac.uk).

Otherwise, you may apply directly via our How to Apply page mentioning the “CTI iCASE PhD studentship”.