Job description

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Software Developer (Simulation/Digital Twin) (KTP Associate) (3437)

Based at: Blueskytec, Bath

The role:

An exciting opportunity has become available to work full time on an 2-year Knowledge Transfer Partnership (KTP) to develop an AI-Augmented Security capability for IoT-enabled critical national infrastructure.

Company information:

Blueskytec and Manchester Metropolitan University have enjoyed close partnering arrangements for two years specialising in high assurance cryptography, IoT, AI and Digital Twin technology.

Blueskytec are a small technology focused company based in Bath with significant projects with industrial partners and government in the UK and US addressing the needs of future smart and resilient infrastructure, in particular against zero-day cyber-attacks on control systems that form the heart of society and national infrastructure.

This is a unique opportunity to work as a Knowledge Transfer Partnership Associate with experts in cryptography and AI at the labs in Bath, supported by MMU and other partners in academia and industry, and with an opportunity to register for part-time study towards a PhD.  Blueskytec and InnovateUK (Knowledge Transfer Partnership) are funding these positions.  At the heart of the work is HardSec (security in silicon) and a testbed of both virtual and real equipment that emulate future infrastructure and use AI/ML to both attack and optimise future data centric infrastructure - a virtuous cycle.

There are two positions available with PhD opportunities, and this is a great opportunity to make a real difference in both cutting edge research and implementation in some of the most complex environments; paving the way to resilient and sustainable future infrastructure combing the power of AI, cryptography and cyber security.

This is an exciting opportunity for applied research in leading edge technologies transforming tomorrows infrastructure.  These skills are in short supply internationally, the combination of these skills with industrial application experience will ensure the successful candidates have the highest possible earning potential benefitting both the individuals and society for the future.

Qualification we require:

Master's degree in computer science, mathematics, physics or engineering, and have demonstrable experience of programming and development of substantial software projects using modern languages and methodologies.

Application requirements:

  • Strong background in modelling/simulation.
  • Strong background in artificial intelligence (machine and deep learning).
  • Knowledge of data visualization and graphics technologies.
  • Knowledge in computer architectures, data structures and algorithms.
  • Proven ability to write clean, consistent and secure code in Python or similar programming languages.
  • Knowledge of domain specific programming languages.
  • Knowledge of virtualisation, specifically Docker.
  • Have good interpersonal skills including teamwork, communication, organisational, problem solving and management skills.
  • SC security clearance would be a benefit.

Benefits:

  • £2,000 per year to spend on personal training;
  • attendance at two managerial workshops with Ashorne Hill;
  • opportunity to register on a higher degree (at a reduced cost);
  • opportunity of a permanent position with the company; 70% of host companies make a permanent job offer to their Associate at the end of the project.

For an informal discussion, please contact Dr Huw Lloyd (huw.lloyd@mmu.ac.uk), Prof Mohammad Hammoudeh (m.hammoudeh@mmu.ac.uk)  or Prof Bamidele Adebisi (b.adebisi@mmu.ac.uk)

Apply by submitting a CV and covering letter detailing how you meet the criteria for the role at https://manmetjobs.mmu.ac.uk/jobs/


 
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Location
Manchester All Saints Campus
Oxford Road, Manchester, UK, M15 6BH
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  • Location:
    Manchester All Saints Campus
  • Faculty / Function:
    Science and Engineering
  • Salary:
    £30,000 - £33,000 dependent on experience.
  • Closing Date:
    22 April 2021
  • Contract Type:
    fixed term
  • Contracted Hours per week:
    37.5
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