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PhD Opportunities

Trustworthy and Explainable Learning-Enabled Autonomous Systems

School of Electronics, Electrical Engineering and Computer Science | PHD

Applications are now CLOSED
Funding
Funded
Reference Number
CSC/2021/2
Application Deadline
28 February 2021
Start Date
1 October 2021

Overview

Autonomous systems (AS) such as self-driving vehicles are regarded the most trendy and prominent AI applications (especially when considering deep learning). However, their wide deployment is facing a bottleneck because of safety concerns. The existence of crucial deep learning components in the overall system greatly complicates and challenges existing safety road certifications. On paper, there is a large amount of research at learning component level and some research at system level about the safety of autonomous systems. In contrast, most of them have not been validated or applied in the field. Moreover, most trustworthiness related research on real-world autonomous systems is owned by companies. This fact is not in the public interest. Focusing on the challenges brought by the irruption of deep learning in modern society, in this project you are going to develop and deliver publicly accessible AI safety solutions that can be used in real-world scenarios to boost the trustworthiness for autonomous systems. In this project, we aim to bridge the gap between theory and practice for safety assurance of learning-enabled autonomous driving. You will work and validate you approaches on a scaled autonomous vehicle: The F1TENTH Autonomous Vehicle System (https://f1tenth.org/), a powerful and versatile open-source platform for autonomous systems research and education.

Objectives:

1.Explaining the learning-enabled systems

Deep Learning components in an autonomous system are complex non-linear functions with algorithmically generated (and not engineered) coefficients from data, and therefore are effectively “black boxes”. They are given an input and produce an output, but the calculation of these outputs is difficult to explain. The goal of explainable AI is to create artifacts that provide a rationale for why a model generates a particular output for a particular input. This is argued to enable stakeholders to understand and appropriately trust neural networks. In this work, you will investigate automated verification and validation techniques for securing AS having AI, which contributes towards “explainable AI-enabled systems”.

2.Physical adversarial attack

It is well known that deep learning models are vulnerable under adversarial attacks, which craft malicious inputs that fool the model. Though adversarial attacks have been extensively studied in literature, most of the adversarial attacks cannot be simply replicated in the real world. Our recent study on a vehicle tracking system further shows that attacks on the learning component can be compensated by other functional pieces of the system. Though it is almost certain that adversarial attacks on its deep learning component can result in serious injuries and even fatal accidents in autonomous driving, the evidence is still limited (there are reports about using adversarial attacks to cause the accidental speed-up of a car). You will investigate the potential vulnerabilities of autonomous driving when its deep learning module is under adversarial attacks in a real-world scenario.

3.Runtime monitoring and diagnosis

As counter-measurement for the previous attacks, you will design and deploy an adversarial monitoring system that operates when the car is in autonomous mode. Though there have been works on runtime adversarial attacks detecting (in theory), we are not aware of any related work for autonomous driving. The runtime system will keep a track of logs for deep learning related events. When the failure indeed happens, an explainable AI based diagnosis will be used to identify causes for the failure.

Funding Information

Academic Requirements:

A minimum 2.1 honours degree or equivalent in Computer Science or Electrical and Electronic Engineering or relevant degree is required.

GENERAL INFORMATION
This 3 year PhD studentship, potentially funded by the Department for Employment and Learning (DfE), commences on 1 October 2021.

Eligibility for both fees and maintenance (approximately £15,000) depends on the applicants being either an ordinary UK resident or those EU residents who have lived permanently in the UK for the 3 years immediately preceding the start of the studentship. Non UK residents who hold EU residency may also apply but if successful may receive fees only.

Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/

Further information available at: https://www.qub.ac.uk/schools/eeecs/Research/PhDStudy/

Project Summary
Supervisor
Dr Youcheng Sun
Mode of Study

Full-time: 3 years


Funding Body
DfE
Apply now Register your interest

Computer Science overview

The School of Electronics, Electrical Engineering and Computer Science (EEECS) aims to enhance the way we use technology in communication, data science, computing systems, cyber security, power electronics, intelligent control, and many related areas.

You’ll be part of a dynamic doctoral research environment and will study alongside students from over 40 countries world wide; we supervise students undertaking research in key areas of computer science, including: computing systems, artificial intelligence and cybersecurity. As part of a lively community of over 100 full-time and part-time research students you’ll have the opportunity to develop your research potential in a vibrant research community that prioritises the cross-fertilisation of ideas and innovation in the advancement of knowledge.

Many PhD studentships attract scholarships and top-up supplements. PhD programmes provide our students with the opportunity to acquire an extensive training in research techniques.

Within the School we have a number of specialist research centres including a Global Research Institute, the Institute of Electronics, Communications and Information Technology (ECIT) specialising in Cyber Security, Wireless Innovation and Data Science and scalable computing.

Computer Science Highlights
Industry Links
  • Queen’s researchers have strong links with the local industry, which boasts a rich mix of local startups and multi-nationals. Belfast is the second fastest growing region in the UK in terms of Knowledge Economy activity (Northern Ireland Economy Report, 2018).
World Class Facilities
  • The state-of-the-art £14m Computer Science Building and the Institute of Electronics, Communications and Information Technology offer bespoke research environments.
Internationally Renowned Experts
  • You will be working under the supervision of leading international academic experts.
Key Facts

Research students are encouraged to play a full and active role in relation to the wide range of research activities undertaken within the School and there are many resources available including:

  • A wide range of personal development and specialist training courses offered through the Personal Development Programme
  • Access to the Queen's University Postgraduate Researcher Development Programme
  • Office accommodation with access to computing facilities and support to attend conferences for full-time PhD students
Brexit Advice

Information on the implications of Brexit for prospective students.

Course content

Research Information

Associated Research
Research within the School is organised into research themes combining strengths by working together on major projects, in many cases in collaboration with key technology companies.
ECIT brings together internationally recognised research groups specialising in key areas of advanced digital and communications technology.

PhD Opportunities
PhD Opportunities are available in a wide range of computer science subjects, aligned to the specific expertise of our PhD supervisors.

Research Impact
Queen’s is a leader in commercial impact and one of the five highest performing universities in the UK for intellectual property commercialisation. We have created over 80 spin-out companies. Three of these -
Kainos, Andor Technology and Fusion Antibodies - have been publicly listed on the London Stock Exchange.

Research Projects
Queen’s has strong collaborative links with industry in Northern Ireland, and internationally. It has a strong funding track record with EPSRC and the EC H2020 programme.

Research Success
The research profile produced by the 2014 UK Research Excellence Framework (REF) graded 80 per cent of our research activity as 'world-leading' or 'internationally excellent', confirming the School's reputation as an internationally-leading department.

Career Prospects

Introduction
For further information on career opportunities at PhD level please contact the Faculty of Engineering and Physical Sciences Student Recruitment Team on askEPS@qub.ac.uk. Our advisors - in consultation with the School - will be happy to provide further information on your research area, possible career prospects and your research application.

People teaching you




Learning Outcomes

Course structure

There is no specific course content as such. You are expected to take research training modules that are supported by the School which focus on quantitative and qualitative research methods. You are also expected to carry out your research under the guidance of your supervisor.

Over the course of study you can attend postgraduate skills training organised by the Graduate School.

You will normally register, in the first instance, as an ‘undifferentiated PhD student’ which means that you have satisfied staff that you are capable of undertaking a research degree. The decision as to whether you should undertake a PhD is delayed until you have completed ‘differentiation’.

Differentiation takes place about 8-9 months after registration for full time students and about 16-18 months for part time students: You are normally asked to submit work to a panel of up two academics and this is followed up with a formal meeting with the ‘Differentiation Panel’. The Panel then make a judgement about your capacity to continue with your study. Sometimes students are advised to revise their research objectives or to consider submitting their work for an MPhil qualification rather than a doctoral qualification.

To complete with a doctoral qualification you will be required to submit a thesis of approx 80,000 words and you will be required to attend a viva voce [oral examination] with an external and internal examiner to defend your thesis.

A PhD programme runs for 3-4 years full-time or 6-8 years part-time. Students can apply for a writing up year should it be required.

The PhD is open to both full and part time candidates and is often a useful preparation for a career within academia or consultancy.

Full time students are often attracted to research degree programmes because they offer an opportunity to pursue in some depth an area of academic interest.

The part time research degree is an exciting option for professionals already working in the education field who are seeking to extend their knowledge on an issue of professional interest. Often part time candidates choose to research an area that is related to their professional responsibilities.

If you meet the Entry Requirements, the next step is to check whether we can supervise research in your chosen area. We only take students to whom we can offer expert research supervision from one of our academic staff. Therefore, your research question needs to engage with the research interests of one of our staff.

Assessment

- Assessment processes for the Research Degree differ from taught degrees. Students will be expected to present write up their work at regular intervals to their supervisor who will provide written and oral feedback; a formal assessment process takes place annually.

This Annual Progress Review requires students to present their work in writing and orally to a panel of academics from within the School. Successful completion of this process will allow students to register for the next academic year.

The final assessment of the doctoral degree is both oral and written. Students will submit their thesis to an internal and external examining team who will review the written thesis before inviting the student to orally defend their work at a Viva Voce.

Feedback

- Supervisors will offer feedback on the research work at regular intervals throughout the period of registration on the degree.

Facilities
Full time PhD students will have access to a shared office space and access to a desk with personal computer and internet access.

Entrance requirements

Graduate
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.

International Students

For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements

Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component or equivalent qualification acceptable to the University is required (*taken within the last 2 years).

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.

As a result of the COVID-19 pandemic, we will be offering Academic English and Pre-sessional courses online only from June to September 2020.

  • Academic English: an intensive English language and study skills course for successful university study at degree level
  • Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.

Tuition Fees

Northern Ireland (NI) 1 £4,500
Republic of Ireland (ROI) 2 £4,500
England, Scotland or Wales (GB) 1 £4,500
EU Other 3 £22,000
International £22,000

1 EU citizens in the EU Settlement Scheme, with settled or pre-settled status, are expected to be charged the NI or GB tuition fee based on where they are ordinarily resident, however this is provisional and subject to the publication of the Northern Ireland Assembly Student Fees Regulations. Students who are ROI nationals resident in GB are expected to be charged the GB fee, however this is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.

2 It is expected that EU students who are ROI nationals resident in ROI will be eligible for NI tuition fees, in line with the Common Travel Agreement arrangements. The tuition fee set out above is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.

3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.

All tuition fees quoted are for the academic year 2021-22, and relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.

For further information please refer to www.qub.ac.uk/brexit-advice/information-for-students.

More information on postgraduate tuition fees.

Computer Science costs

There are no specific additional course costs associated with this programme.

Additional course costs

All Students

Depending on the programme of study, there may also be other extra costs which are not covered by tuition fees, which students will need to consider when planning their studies . Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £100 per year for photocopying, memory sticks and printing charges. Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen. There are also additional charges for graduation ceremonies, and library fines. In undertaking a research project students may incur costs associated with transport and/or materials, and there will also be additional costs for printing and binding the thesis. There may also be individually tailored research project expenses and students should consult directly with the School for further information.

How do I fund my study?
1.PhD Opportunities

Find PhD opportunities and funded studentships by subject area.

2.Funded Doctoral Training Programmes

We offer numerous opportunities for funded doctoral study in a world-class research environment. Our centres and partnerships, aim to seek out and nurture outstanding postgraduate research students, and provide targeted training and skills development.

3.PhD loans

The Government offers doctoral loans of up to £26,445 for PhDs and equivalent postgraduate research programmes for English- or Welsh-resident UK and EU students, £10,000 for students in Scotland and up to £5,500 for Northern Ireland students.

4.International Scholarships

Information on Postgraduate Research scholarships for international students.

Funding and Scholarships

The Funding & Scholarship Finder helps prospective and current students find funding to help cover costs towards a whole range of study related expenses.

How to Apply

Apply using our online Postgraduate Applications Portal go.qub.ac.uk/pgapply and follow the step-by-step instructions on how to apply.

Find a supervisor

If you're interested in a particular project, we suggest you contact the relevant academic before you apply, to introduce yourself and ask questions.

To find a potential supervisor aligned with your area of interest, or if you are unsure of who to contact, look through the staff profiles linked here.

You might be asked to provide a short outline of your proposal to help us identify potential supervisors.