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Sign up for the New Queen’s University Belfast’s funded research program for a chance to receive a unique opportunity to explore the challenges of Artificial intelligence (AI) for every area of science and society.

Thirty funded postdoctoral scholarships will be awarded by the program, and researchers who secure places on the program will work at the cutting edge of AI algorithms while considering the societal implications of allowing machines to make decisions about the future.

Application Deadline: March 5, 2021.

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Benefits

The Scholarship includes:

  • Full-time postgraduate research tuition fees at Standard UK Rates (not yet set for 2021/22). 
  • A maintenance award at the Research Councils UK national rate
  • Research Training and Expenses.

Eligibility

To qualify for consideration in the scholarships, Applicants must have:

  • A good honours degree ( at least a 2.1 or equivalent in a relevant subject )which will include 
    • physics, 
    • maths, 
    • computer science 
    • law, 
    • social science, and 
    • the humanities. 
  • preferably also a Masters qualification, and 
  • a commitment to interdisciplinary approaches.

Requirements/Specifications 

  • Within this program, PhD applicants will work with named researchers across the relevant disciplines on a proposal that fits within the overall program.  
  • Applicants must establish contact with their potential supervisor to develop their ideas about how they would contribute to the proposed project.  

The application should detail the particular contribution that the potential doctoral scholar would make to the proposed project, how this would fit into the wider themes of the program and whether the application is for a three or four year award.

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Application Instructions

Before applying, Note: 

  • All applications must be directed to the School where the Primary Supervisor is based. 
  • They must also be clearly marked as LINAS 21 to ensure consideration for funding. 

Failure to include the reference LINAS21 in the free text box may result in your application not being allocated or considered for funding.

  • Choose the option in the funding section “I wish to be considered for external funding” and then enter LINAS21 in the free text box which follows.

To apply,

  • Provide:
    • An up-to-date CV- this should be uploaded to the Admissions Portal as a separate document*
    • A 2000 word research proposal, specifically detailing how your PhD will address the interdisciplinary aspects of the LINAS programme

Applicants wishing to propose an interdisciplinary PhD topic of their own, that aligns with one or more of the LINAS priority themes, must upload a 2000 word research proposal that describes the topic as a separate document.* 

This research proposal must clearly identify a potential supervisory team and which of the themes it relates to

*Only one document can be uploaded. You must combine your CV and Research Proposal into one document (word or PDF).

  • Click here to apply.
  • The LINAS Academic Team:
  • Register your interest in the virtual information session here. 

About the Queen’s University LINAS Doctoral Training Program

The Queen’s scholarship opportunities was launched to explore the impact of Artificial Intelligence on science and society.

Queen’s University Belfast provides thirty funded postdoctoral scholarships to advance a unique opportunity to explore the challenges of Artificial intelligence (AI) for every area of science and society.

Awarded a Leverhulme Doctoral Scholarship grant of £1.35m over six years for the Leverhulme Interdisciplinary Network on Algorithmic Solutions (LINAS) Doctoral Training Program (DTP) to fund 15 doctoral scholarships, Queen’s matched the funding to sponsor another 15 positions over the next three years.

The interdisciplinary research program will be supervised by academic experts from the Faculty of Arts, Humanities and Social Sciences and the Faculty of Engineering and Physical Sciences. 

The program will be led by Professor John Morison from the School of Law, along with Dr Sandra Scott-Hayward from the School of Electronics, Electrical Engineering and Computer Science, and Professor Stephen Smartt from the School of Maths and Physics at Queen’s.

The LINAS project will identify and address scientific and engineering questions through the lens of law, humanities and the social sciences. Researchers will scrutinise the implications of algorithmic solutions on crucial aspects of human life.

Researchers from the Faculty of Engineering and Physical Sciences and the Institute of Electronics, Communications and Information Technology (ECIT) will engage directly with humanities, social science and law researchers from the Senator George J. Mitchell Institute for Global Peace, Security and Justice to support the doctoral scholars.

The Project priority themes are:

  • Artificial Intelligence, Social Justice and Public Decision-Making
  • Algorithmic accountability: Public control of AI decision-making
  • Legal and social-legal challenges around new technology
  • AI and Humans: Reckoning and Judgement
  • Fairness in Exploratory Data Analytics: The agency shift from humans to AI
  • Science, Governability and Society
  • Robotic eyes on the sky and on earth
  • ML-enhanced quantum information processing
  • Numerically Robust and Reproducible Deep Learning
  • Algorithmic security: Distributed Agency, Responsibility, and Governability

Key Dates and Order of Program

The deadline for application is 5th March 2021 at 4.00 pm.

Interviews will commence by 15th March 2021.

Selection decision will be made known to applicants starting by 9th March 2021.

The virtual information session will take place on 18th February 2021.

Three or four year studentships are available.

Selection will be made based on merit.

An information session will take place and it will be provided digitally.

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Babajide is a content writer and site admin at Camberene. He majored in zoology and is also a tech enthusiast proficient in the use of python, R and other data analytics tools.

Babajide is looking into using machine learning and artificial intelligence in the near future.