NPIF PhD Studentships - Artificial Intelligence and Data-Driven Research

NPIF PhD Studentships - Artificial Intelligence and Data-Driven Research

With support from the Arts and Humanities Research Council (AHRC) and the National Productivity Investment Fund (NPIF), we are delighted to announce three PhD studentships for projects focusing on Artificial Intelligence and Data-Driven Research.

These studentships involve SGSAH, AHRC, HEIs and organisations. They seek to connect HEIs, organisations and a PhD researcher on a project of mutual benefit to all involved related to Artificial Intelligence and/or Data-Driven Research. They present an opportunity to work on a fascinating research project, make connections with industry and access resources and expertise not normally available within a PhD.

The projects below have been identified by the HEI and the industry partner ensuring that your work is fulfilling a research need already noted by an organisation in the sector. Working with an organisation outwith academia will offer unique training and development opportunities of benefit to the PhD and your own personal development.

Also, you will be eligible for the range of SGSAH training and development opportunities including our annual Summer School, Research Showcase and student-led collaborative training funds as well as our entrepreneurial training for arts and humanities doctoral researchers.

Applications are handled by the individual HEIs.

Application deadlines are invidual to each project. Please take note of these prior to applying.

Eligibility

To be eligible to apply you must:

  • Meet the residency criteria set out by UKRI.
  • Be prepared to live within a reasonable distance of the lead HEI.  We define a reasonable distance as follows: a student ought if necessary to be able to travel to the University every day to work core hours (10am to 4pm).

The AHRC also expects that applicants to PhD programmes will normally hold, or be studying towards, a Masters qualification. If you are not in this position you may be able to use relevant professional experience to provide evidence of your ability to undertake independent research.

Residency criteria

The following is taken from the UKRI Conditions of Research Council Training Grants document, p17.

“For purposes of residence requirements, the UK includes the United Kingdom & Islands (i.e. the Channel Islands & the Isle of Man). 

  • There are residence requirements for research council funding for postgraduate research. These are based on the Education (Fees and Awards) (England) Regulations 2007 and subsequent amendments Normally to be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship (with some further constraint regarding residence for education).

The UK Government confirmed on 21 April 2017 that Research Council studentships (including AHRC studentships awarded through the Scottish Graduate School for Arts & Humanities) remain open to EU students starting courses in academic year 2018 to 2019, & that the funding support will cover the duration of their course, even if the UK leaves the EU.


Artificial Intelligence (AI) and the assessment of data sensitivity in cultural organisations

Title 

Artificial Intelligence (AI) and the assessment of data sensitivity in cultural organisations: an exploration of the possibilities and implications in the context of a memory institution, the National Library of Scotland (NLS).

Partners 

University of Glasgow, National Library of Scotland

Eligibility

Open to:

  • UK candidates with fee waiver and stipend at current UKRI rate
  • EU applicants on a fees only basis 

 Candidates should possess at least a 2:1 (or equivalent) in their undergraduate degree and should normally have completed or be currently completing a Master’s degree in a relevant subject.

An understanding of artificial intelligence for information analysis and management will be essential. Knowledge of the technical aspects of AI is not essential but evidence of programming (e.g. Python, R) and data analysis skills (e.g. statistics) is required. Enthusiasm for interdisciplinary research (e.g. across artificial intelligence, law, digital curation, information science), and, ability to work both independently, and, as part of a team, is also essential.

The successful candidate will be required to spend at least 6 months across the studentship at the National Library of Scotland (NLS) in Edinburgh. To make this possible additional support will be provided by NLS.

Supervisors

Dr Yunhyong Kim, University of Glasgow

Professor Seamus Ross, University of Glasgow

Dr Pauline McBride, University of Glasgow

Collaborating Partners

Lee Hibberd, Digital Preservation Officer, National Library of Scotland

Stephen Rigden, Digital Archivist, National Library of Scotland

Fred Saunderson, Rights and Information Manager, National Library of Scotland

Project Description

With support from Arts and Humanities Research Council (AHRC) and the National Productivity Investment Fund (NPIF) through the Scottish Graduate School for Arts and Humanities (SGSAH), Information Studies at the University of Glasgow, in collaboration with the National Library of Scotland, seeks a highly motivated graduate to undertake Ph.D. research, to investigate the effectiveness and appropriateness of using artificial intelligence (AI) for reviewing data for diverse forms of sensitivity at the National Library of Scotland.

The research will use innovative methods for handling sensitive information, focusing on compliance with legal obligations (e.g. data protection). It will also investigate broader concerns, such as cost and data ethics of incorporating AI in data handling, recommending guidelines for using AI as a component for scalable policies regarding sensitive data at the Library.

Recent developments in data protection law (e.g. the General Data Protection Regulation (GDPR)) require renewed action from all sectors (academic, industry, government and cultural organisations), including the National Library of Scotland, for the assessment of the means and methods of compliance. The rapid increase in data volumes over the last three decades, however, makes meeting legal obligations, while maintaining continued improvement of trusted services provided to citizens, a hard task to achieve, without the employment of scalable artificial intelligence techniques (e.g. information retrieval, natural language processing, machine learning). Hitherto computing science has been perceived as the venue for such artificial intelligence research. The research proposed here endeavours to broaden participation to the arts and humanities and cultural organisations such as National Library of Scotland.

The project aims to improve workflow productivity within memory institutions through the incorporation of AI (e.g. machine learning, natural language processing, information retrieval) in data and documentary content analysis. This will involve experimentation and a comprehensive exploration of artificial intelligence as a means of reviewing data and supporting policies regarding sensitive data. While some categories of sensitivity, such as in relation to personal data, may be understood through legal definitions, there can be considerable uncertainty when it comes to defining broader concepts of sensitive information, which can be subject to factors such as cultural and temporal climates. All forms of sensitive content, however, can be extremely challenging to identify or isolate.

The proposed project investigates AI responsive to such uncertainty, to complement human decisions about sensitivity. The research will explore four primary questions:

  1. What is the viability of applying AI enabled learning technologies to the analysis of data and documents to adjudicate concerns about their public release?
  2. What levels require reviewing (e.g. collection, objects, segments), how do these map to changing areas of policy (e.g. GDPR), and what type of material (e.g. images, text, audio, video) need accommodating?
  3. What are the social concerns regarding AI as a means of carrying out personal/sensitive data review, and how can we evaluate their ability to address these concerns?
  4. How feasible is adaptive human-AI collaboration for protocol development beyond the identification of sensitive data? What are the costs, limitations and opportunities?

The research will first test existing approaches on the data/documents (possibly to include non-textual and/or Scots/Gaelic material) at the National Library of Scotland to assess their ability to address these broader definitions, with a wider scope of features. Later, approaches that allow the AI to learn features in changing contexts will be explored. The project will make direct recommendations to inform the Library’s policies, exploring applicability to other sectors. Assessing social implications of AI strengthens adoptability.

For more information see the full project description at the bottom of the page.

This project is subject to National Productivity Investment Fund award conditions.

Applications have now closed

Interviews: 31 July 2018

Start Date: September 2018


Applying Design Thinking to the development of Ethical AI in Accounting

Title

Applying Design Thinking to the development of Ethical AI in Accounting

Partners

University of Edinburgh, The Institute of Chartered Accountants for England and Wales (ICAEW)

Supervisors

Dr Ewa Luger, University of Edinburgh

Collaborating Partners

Martin Martinoff, The Institute of Chartered Accountants for England and Wales

Project Description

Accounting is one of the latest professions to incorporate Artificial Intelligence (AI) in their practice. Currently, only large companies have capacity to make meaningful, resourced choices about how and when to do this. There is also great interest in AI amongst Small to Medium sized Enterprises (SMEs), set against rising concerns over the ethical implications of such adoption. This research focuses on understanding AI adoption, particularly amongst SME accounting firms, in order to co-produce a series of instruments and methods to (a) enable accounting firms to understand the ethical implications of the technology before they adopt, and (b) inform the development of skills and professional training around ethical application of AI. Drawing from design thinking, the candidate would take a creative approach to supporting exploratory thinking about the ethical benefits and implications of AI.

Eligibility

It is anticipated that the successful applicant would have a first-class degree or good 2:1 and a Masters or equivalent experience in Ethics, Social Science, Human-Computer Interaction, Interaction Design, or an area cognate to the project. Good written and spoken English is essential. A sound understanding of social research and the ability to conduct studies with human subjects is desirable, as is the ability to convert research findings into design guidelines and principles. 

To be eligible for a NPIF Artificial Intelligence studentship, you must meet AHRC eligibility criteria.

Unfortunately, we are not able to fund international students. EU students are eligible for fees-only awards.

Essential:

  • First or upper-second class honours degree or equivalent
  • Masters-level degree (or equivalent experience) in a cognate area, e.g. Ethics, Philosophy, Design, Social Science, Artificial Intelligence
  • Demonstrable ability to work independently and willingness to work with the ICAEW for six months across the course of the project
  • A real and demonstrable interest in the ethics of machine/artificial intelligence and/or the accounting profession
  • Willingness to engage with a broad range of audiences to disseminate the work
  • Willingness to travel to ICAEW (London, UK) as required

Desirable:

  • An understanding of ethics, machine learning or the accounting profession
  • Knowledge and understanding of contemporary challenges arising from socio-technical systems
  • Experience of fieldwork (ethnographic/interview/observation)
  • Experience of developing Design interventions

Applicants will need to meet the requirements of postgraduate studies at the University of Edinburgh.

Whilst the PhD will be based at the University of Edinburgh, during the project the scholar will be expected to spend six months based in London with theInstitute of Chartered Accountants for England and Wales (ICAEW).

Applications have now closed

Interviews: provisionally scheduled for early August 2018

Start Date: September 2019


What We Dream Comes to Fruition: Diversity, Artificial Intelligence, and Science Fiction

Title

What We Dream Comes to Fruition: Diversity, Artificial Intelligence, and Science Fiction

Partners

University of Dundee, Defence Science and Technology Laboratory (DSTL), Craft Prospect

Supervisors

Dr Nicole Devarenne, Univesity of Dundee

Prof Annalu Waller, University of Dundee

Collaborating Partners

Amanda Shakir, BSc, FRAeS, Defence Science and Technology Laboratory

Dr John Carney, Defence Science and Technology Laboratory

Overview: 

Representations of AI in science fiction influence how technologies develop and how the general public interacts with them. A lack of diversity is a problem both in SF and in the UK’s AI industry. Inclusive worlds exist in SF, but largely on the periphery of academic scholarship and popular culture trends. Understood broadly, ‘design’ which is more sensitive, inclusive, and adaptable should be a gold standard for creative practice, scholarship, and software development alike. This project draws upon a broad range of SF narratives to inspire the development of more accessible technologies, broaden participation and inform public debate about AI.

The aims and objectives of the studentship are:

  1. With a focus on diversity in AI, to initiate a new flow of ideas across academic disciplines (Humanities and Computing), and between academia and UK government
  2. To share the benefits of this knowledge exchange with industry and the general public, through public engagement activities and by interfacing with AI industries
  3. To contribute to the common good and enhance UK security through a better understanding of the importance of diversity in the AI workforce and in AI design
  4. Depending on the background and interests of the student, to produce an original and innovative doctoral thesis that would (as examples):
  • document the cultural factors involved in the problematic representation and under-representation of diversity in SF;
  • describe how overlooked or new forms of narrative could inspire new directions in software design or the public relationship with AI;
  • produce a series of case studies relating the representation of AI in SF to software design manifestations in the real world, and propose alternatives through imaginative thinking;
  • approach software design problems using analytical methodologies drawn from the Arts & Humanities, with the aim of enhancing accessibility and usability 

The research questions are:

  • How can science fiction narratives inspire design strategies that prioritise usability for a diverse national community?
  • How can SF narratives influence the design of more sensitive, inclusive and adaptable AI?
  • How might exposure to a wider range of narratives encourage the development of a more diverse workforce in the AI industry?
  • How can we better educate and inform the general public about the moral, legal, and ethical concerns surrounding AI, with a special emphasis on diversity, accessibility and inclusion?
  • How can design goals prioritising diversity help grow the AI industry in the UK and enhance our security and prosperity?

Research Environment

The studentship is jointly supervised by Dr Nicole Devarenne in Humanities and Professor Annalu Waller in Computing at the University of Dundee. We will be working with two non-academic partners: Dstl (Defence Science and Technology Laboratory) and Craft Prospect. Please see below for more information on our partners.

The University of Dundee offers the only science fiction master’s degree in Scotland, drawing upon staff’s wide-ranging expertise in science fiction literature, film and comics. Humanities’ Scottish Centre for Global History provides an internationally-focused research environment. Humanities also houses the Scottish Centre for Comics Studies and has been the Scottish hub for the UK’s Being Human Festival of the Humanities since 2015. We host a regular postgraduate forum, visiting speakers and an annual postgraduate conference.

Computing at Dundee has an emphasis on Human Centred Computing and Intelligent Systems across a wide range of fields, and addresses real world problems. Staff have expertise in artificial intelligence, with research interests and initiatives in artificially intelligent games; argumentation; cryptographic protocols; computer vision, pattern recognition and machine learning methods; augmentative and alternative communication; and accessible computing. Computing at Dundee welcomes, and is accustomed to, interdisciplinary work.

Dstl (Defence Science and Technology Laboratory) is the UK’s leading government agency in applying science and technology (S&T) to the defence and security of the UK. Dstl brings together the defence and security S&T community, including industry, academia, wider government and international partners, to provide sensitive and specialist S&T services to the Ministry of Defence and wider government. It seeks to understand risks and opportunities through horizon-scanning, and champions and develops science and technology skills across MOD.

Craft Prospect is an SME with offices in Glasgow and Edinburgh, specialising in enabling technology systems for small satellites. Their staff have lead and developed small satellite systems in Europe and Asia for new mission concepts.  Products include a forward imager that makes real-time, on-board decisions for a satellite, influencing data set collection. A social enterprise working closely with Craft Prospect staff, Omanos Analytics, looks to support citizen journalists in developing countries as they process and interpret AI-based knowledge (earth observation data).

Supervision, Training and Facilities

Academic supervisors will work with the student to ensure that research outputs and public engagement activities effectively support the research outcomes, objectives and impacts. In accordance with the agreement between the HEI members of the SGSAH consortium, the student will have formal meetings with the lead supervisor at least ten times per year and with both supervisors at least five times per year. Frequent meetings with Dstl will take place by telephone or Skype, and the student will work on-site with our non-academic partner(s).

The University of Dundee will supply supervision of the student. It will also provide the student with all facilities available to the doctoral student community. These include a well-stocked library, on-line research resources, archive facilities, a research space, training in research methods and a vibrant research community. The student will interact with internationally established researchers and international research visitors through the AHRI (Arts and Humanities Research Institute). The Centre for Creative and Critical Cultures also offers a series of events. The student will have access to academic and personal support services.

Dstl will provide support for the researcher in terms of mentoring, sharing expertise, and offering access to their programmes and initiatives.

Some travel, including international travel, is anticipated. The student will be supported in terms of their attendance at training events organised by SGSAH.

Eligibility

To be eligible for a NPIF Artificial Intelligence studentship, you must meet AHRC eligibility criteria. http://www.ahrc.ac.uk/documents/guides/training-grant-funding-guide-2015-16/

Along with fulfilling the AHRC’s eligibility requirements for a +3 doctoral studentship, the successful candidate is likely to come from an Arts & Humanities background, with an interest in science fiction. Other academic backgrounds may also be suitable – please send enquiries to the address below. Effective communication skills are essential. An interest in creative writing would be considered an advantage, as would experience or interest in software design.

Unfortunately, we are not able to fund international students. EU students are eligible for fees-only awards.

Funding

The award is offered for full time registration for the PhD. For UK nationals, the funding will include a tax-free stipend of £15,327, and tuition fees. 

How to apply

To be considered for a NPIF Artificial Intelligence studentship please complete the form and submit it with your application to UCAS at https://digital.ucas.com/courses/details?coursePrimaryId=501eb668-da7a-a068-acc8-d0dd6017d212

University of Dundee - NPIF AI Application Form

You should attach two references with your application, or ask your referees to send these to n.devarenne@dundee.ac.uk.

Enquiries can be directed to n.devarenne@dundee.ac.uk.

Deadline for applications and references is 5 pm on 24 August 2018.

It is anticipated interviews will be held in early September.