PhD Studentship in Performance and Scalability Optimization of Blockchain based FinTech Infrastructure

The University of Edinburgh - School of Informatics

Do you want to obtain a PhD degree in 3.5 years at School of Informatics (QS World Ranking 14 in 2017), University of Edinburgh with fully paid tuition fees and a generous annual stipend?  If yes, then please read below:

Deadline: 31 July 2018

PhD Studentship in Performance and Scalability Optimization of Blockchain based FinTech Infrastructure.

Collaborative Awards in Science and Engineering

The aim of this scholarship award is to provide exceptional PhD candidates with a first-rate, challenging research training experience, within the context of a mutually beneficial research collaboration between academic and partner organisations e.g. industry and technology firms. The scholarship provides outstanding students access to training, facilities and expertise. Students benefit from a diversity of experimental approaches with an applied/translational dimension. Students have an opportunity to develop a range of valuable technical and mathematical skills and significantly enhance their future employability; many will become research leaders of the future.

Project Description

The aims of the project are to: (i) Adopting the state-of-the-art deep learning and behaviour prediction models to look at mobile users’ behaviour for financial applications; (ii) develop cloud-based Fintech infrastructures for developing App-Cloud prediction framework. The Award holder will be located in the Centre for Intelligent Systems and their Applications, School of Informatics at the University of Edinburgh (further details below).  

Centre for Intelligent Systems and their Applications, School of Informatics, University of Edinburgh

Supervisors: Dr. Tiejun Ma

Expected Start Date:  September 2018

Entry Requirements:

The normal minimum entrance requirement is:

  • A good Masters degree from a leading UK university or equivalent overseas/professional qualification in an appropriate subject or a First Class honours BSc in exceptional cases.

Please refer to the following link for details:

Background/Skills Required:

Detailed understanding and knowledge of at least two of the following:

  • Computer Science/Computing/Behavior OR/Management Science
  • Mathematics/Probability/Behavior Data Analytics/Machine Learning.
  • Strong JAVA software development skills is essential.
  • Experience with behavior data analytics
  • Skills of Cloud computing is a plus
  • Good knowledge about data mining algorithms/tests (e.g. SVM, NN, Deep Learning, Survival Analysis, Logistic Regression, DL4J/Tensorflow)
  • Knowledge about probability, statistics, Matlab/R/Python is a plus but not necessary.

How to Apply

If you have any questions about the studentship or application process or enquiries about the project itself, please email: Dr. Tiejun Ma (;

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