Research Fellow (Malware Detection on Online Banking) x2 Posts

London Metropolitan University - School of Computing and Digital Media

About Us

Callsign - LondonMet Partnership

The Enterprise Partnership between Callsign and London Metropolitan University has been in operation for 1 year and has resulted in several projects in the area of cybersecurity. Its main purpose is to assist the efforts of Callsign to secure its operations through providing expertise and dedicated resources for tackling the difficult problems of cybercrime, fraud and security management.

About the Post

This post is fixed term for 12 months.

The School of Computing and Digital Media at London Metropolitan University in partnership with Callsign are currently recruiting for a highly motivated Research Associates to conduct a study of the security aspects of online banking and the methods for identity recognition and authentication with an emphasis on the application to digital banking.

You will work for two days at the University and three days within a research team at Callsign to carry out research and perform software development activities aimed at supporting Callsign’s efforts to implement an integrated advance authentication controls using techniques such as Malware Detection. You will be expected to develop machine learning / deep learning based software system for assisting the risk based authentication framework developed by Callsign and after completing the work may be offered a permanent position within Callsign.

Job Benefits Include:

  • working on the forefront of the technical development in cybersecurity
  • being part of the research team at Callsign and researching/implementing on the bleeding edge AI research
  • developing creativity and innovative thinking
  • interacting with high calibre specialists within professional environment
  • highly competitive salary 

The Candidate

You will be a graduate with a BSc/MSc in Computer Science, IT, Software Engineering, Applied Mathematics or Statistics. An MSc or PhD in computer science, machine learning or Statistics could be a benefit. You will have experience in the following:

  • Expert in applied mathematics and statistics (i.e. information theory, information science, etc.)
  • Expert in methodologies for supervised, un-supervised or semi-supervised learning (i.e. clustering, gaussian processes, RNN, LSTM, etc.)
  • Working knowledge and practical skills in using tools for object-oriented programming (i.e., Java, Python)
  • Professional skills for software development (including testing and documentation)

An additional advantage would be the acquaintance with the business processes in digital banking and some knowledge of the principles and methods for fraud detection, cybersecurity and security management.

For this challenging and demanding role you must be highly motivated and a good team player whilst able to work on your own initiative. You will be a confident communicator able to relate to colleagues at all levels including company board members and must have excellent verbal and written communication skills.

For informal enquiries contact Prof. Karim Ouazzane at or on 020 7133 4306

The Research Associate will be employed by London Metropolitan University under the terms and conditions of the collaborative project between London Metropolitan University and Callsign. 


To apply, please click on the Apply button below. For further information please visit our website at and quote the reference number.

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