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Funded PhD Opportunity

Mapping the Brain with Zero Knowledge using advanced AI and Data Analytics

Subjects: Computer Science and Informatics and Computer Science and Informatics


Summary

Mapping biological networks of the human brain remains one of the complex endevaours in human history. Connectomics is a field of study that aims to map all neural connections in the brain (estimated to be 100 trillion) using MRI, fMRI and EM images obtained from various projects under the Human Connectome Project. Unfortunately, these microscopic neuroimages come in wide variety of sizes, rotations and colours. Spliced 2D images of various segments of the brain with non-standardised fluorescent labelling have to be assembled into a three dimensional representation, in order to understand the neural connectivity (comprising of billions of neurons). To ensure high labelling accuracy, manual tracing (by neuroscientists) remains the gold standard in deciphering these neural connections. This is a time-consuming, trivial and labor-intensive task especially when we consider the number of plausible connections at the microscale resolution.

A citizen scientist initiative to gamify this annotation process was launched in 2012 (Eyewire) with the aim of mapping the retinal neurons. The game has attracted more than 100,000 participants from all over the world. Gamers are tasked with tracing a neuron and its connections based on images of brain slices obtained from a brain tissue. The reconstruction of this branch is validated by experts for its accuracy. Concurrently, the human tracing behaviour is adapted to an AI engine in an effort to improve the automatic annotation capability. Although the activity is simplistic and does not require prior scientific knowledge, this is not your average colouring exercise (i.e., where keeping it inside the line would suffice). There is a minimal training required before your work can be accepted.

On the one hand, the task seems trivial and is highly suited for machine learning adoption, however, the intricacies of tracing the path interconnecting these neurons require innate human traits unknown to conventional supervised learning algorithms. The amount of unannotated data further limits the capability of supervised machine learning approaches for this task. On the other hand, reinforcement learning (RL) might provide a better alternative. Rapid progress has been achieved in developing computer gamers through utilisation of deep neural networks trained using RL paradigms. Advanced RL approaches exemplified by AlphaGo Zero (and its variants) and OpenAI have demonstrated that these systems outperform the best human players in their specialised domains (e.g., Go, Chess, Shogi, 3D games, and other RPG computer games).

RL learns by competing against another agent (could be human or another machine) and in principle does not rely on the availability of labelled data for training. Is it possible to extend the capability of RL to map the human brain? The ability to accurately map our brain carries a significant impact for the future of mankind. Notwithstanding this grand contribution, the proposed research will contribute to further understanding in the area of neuroscience and may result in the development of newer approaches in AI and data analytics towards artificial general intelligence.


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Experience using research methods or other approaches relevant to the subject domain
  • Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project
  • A demonstrable interest in the research area associated with the studentship

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.

  • First Class Honours (1st) Degree
  • Masters at 70%
  • For VCRS Awards, Masters at 75%
  • Publications - peer-reviewed
  • Experience of presentation of research findings
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:

    Vice Chancellors Research Studentship (VCRS)

    Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant 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.

    Vice-Chancellor’s Research Bursary (VCRB)

    Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant 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.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    Fees only award (PhD fees + RTSG for 3 years).

    This scholarship will cover full-time PhD tuition fees 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.

    Department for the Economy (DFE)

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,009 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. 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.

    Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies


Other information


The Doctoral College at Ulster University


Reviews

Profile picture of Adrian Johnston

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Friday 7 February 2020

Interview Date
23 to 24 March 2020


Applying

Apply Online  


Campus

Magee campus

Magee campus
A key player in the economy of the north west


Contact supervisor

Dr Effirul Ramlan


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