PhD Study : Knowledge-based Machine Learning

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Summary

Machine learning is a driver of the current resurgence of artificial intelligence and is playing increasingly important roles in some computer systems in our daily lives. Machine learning is typically entirely data driven; thus, it has some limitations. One limitation is the lack of an ability with a traditional machine learning system to explain its outputs, which has fuelled recent research in explainable AI. Another limitation is the lack of an attention facility to solve well known problems such as the “cocktail party problem”, which has motivated recent research in attention mechanisms in deep learning.

This project will study knowledge-based machine learning, i.e., both knowledge and data are used in the process of machine learning, where knowledge provides the model structure and data determines the model parameters. The knowledge may be guidelines, domain ontologies, or characterisation of objects. It is expected that a knowledge-based learning system will have innate capabilities for explanation and attention.

This project provides an opportunity to combine cutting edge research at the intersection of knowledge and machine learning to address the above key challenges. The timeliness of this PhD project becomes also apparent in the potential of the above integration to contribute to the long-standing goal of explainable and interpretable AI.

This project will investigate fundamental research questions about knowledge-based learning and will be guided by various application scenarios where rich domain knowledge exists:

  1. Computer assisted teaching and learning, where knowledge may be subject ontologies or knowledge graphs;
  2. Spectral pattern recognition, where knowledge may be characterisation of a particular object (e.g. SARV-CoV-2 virus);
  3. Medical decision making, where knowledge may be clinical guidelines (e.g., nice.org.uk); and
  4. Multimedia search, where knowledge may be the structure of a particular media type.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • For VCRS Awards, Masters at 75%
  • Sound understanding of subject area as evidenced by a comprehensive research proposal
  • Publications record appropriate to career stage

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

  • Full Award: (full-time tuition fees + £19,000 (tbc))
  • Part Award: (full-time tuition fees + £9,500)
  • Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

  • Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
  • Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
  • Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
  • Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living

The Doctoral College at Ulster University

Key dates

Submission deadline
Friday 5 February 2021
12:00AM

Interview Date
Week Beginning 22nd March 2021

Preferred student start date
Mid-September 2021

Applying

Apply Online  

Contact supervisor

Dr Jun Liu

Other supervisors