Vacancies for Research Engineers

If you are a Prospective Industry Sponsor and would like to list a vacancy on this page, please contact

If you are a prospective Research Engineer, you can apply here.

Ref: payfont-2016-01


Payfont Limited (Payfont) is a leading Cybersecurity company based in Edinburgh, UK. As of May 2016, Payfont has designed, patented, validated and developed two Cybersecurity frameworks that deliver verifiable breakthroughs in identity protection and data security.

We list below a vacancy we will fund for a Research Engineer (RE), to be recruited via the EngD Computer Science Programme at the School of Computer Science, University of St Andrews.

We seek an enthusiastic RE to work in the area of highly secure and reliable Cloud-based data storage architectures, building on our innovative IP. Specific research work to be performed as part of this funded EngD project will include:

  • Investigating secure and real-time fragmentation of massive enterprise big data using MapReduce frameworks within a virtualised environment;
  • Optimising C++ mathematical and crypto libraries on specific hardware platforms, so as to obtain high-performance and high-throughput with low overheads;
  • Designing and developing a policy-driven system that affords high dynamism, flexibility and dependability;
  • Evaluating performance of the overall system using scientific and rigorous methodologies, and obtaining precise and reproducible benchmark results; and
  • Exploring the potential of the next-generation secure and reliable Cloud-based data storage architectures.

The successful RE will work within our office in Edinburgh, with Dr Lu Fan from Payfont as the Industrial Supervisor.

We would expect a successful applicant to have a strong background in the following:

  • Cloud computing and service-oriented architectures;
  • Data-intensive computation and big data frameworks;
  • Cybersecurity, applied cryptography and coding theory; and
  • C++ programming and performance engineering.
  • Previous experience in collaboration with Payfont would be considered an advantage.

We are confident that the EngD project will result in strong academic impact, as well as direct contributions to Payfont’s core products and growth of business. This will give us a great potential to generate more jobs, including a full-time post for the successful applicant by the end of the EngD project.

Depending on the successful Research Engineer’s contribution to Payfont’s core products, they may be offered full-time employment and an enhanced financial package in year 3 of the four year EngD programme.

Ref: tmvs-2016-01


Toshiba Medical Visualization Systems (TMVS) are based in Edinburgh, where they develop advanced algorithms and tools for medical image analysis. They are part of Toshiba Medical, one of the top four medical imaging companies worldwide, who design and manufacture a wide variety of imaging equipment, including X-ray CT, magnetic resonance imaging, ultrasound imaging, and positron emission tomography. TMVS algorithms are used in these medical scanners and advanced visualization workstations around the world. In a very real sense, these algorithms can save people’s lives.

This project will apply methods from data science, including deep learning and convolutional neural networks, to medical image analysis. Specifically, we wish to identify specific tissue types in the images. For example, can we determine whether a lump is cancer or not without resorting to large biopsy needles? More subtle challenges include being able to distinguish different types of cancer, which is vital in order for doctors to select the best treatment. We could also use the tool to examine the health of important organs such as the lungs, liver and heart. The final aim of the project is the development of a novel clinical application based on these methods.

We would expect a successful applicant to have experience of:

  • Programming, including some experience implementing analysis algorithms (C++, Python, or similar)
  • Machine learning
  • Image analysis (optional, but an advantage)
  • Handling large volumes of data (optional, but an advantage)

The successful RE will work in our office in Edinburgh, as part of the image analysis research team supervised by Dr Keith Goatman. This is a multidisciplinary team consisting of scientists, software engineers, clinical experts, and several EngD students.

Ref: resas-nhsnss-2016-01


The Scottish Government and NHS National Services Scotland have joined up to offer a vacancy for a Research Engineer (RE) to be recruited via the EngD Computer Science Programme at the School of Computer Science, University of St Andrews.

We are looking for an enthusiastic new RE who will work in both organisations during their studies undertaking a number of different data science related projects.

Initially the RE will work on a farm incomes data project with the Scottish Government Rural and Environment Science and Analytical Services (RESAS) to:

  • consider potential sources of information to substitute/complement on-site data collection
  • design farm business income models/forecasts/benchmarking using data mining techniques to overcome time lag of results
  • design and test/implement a system for processing/assessing raw financial data to help inform future options for farm incomes analysis
  • potentially apply similar techniques to different areas within RESAS.

This will require using a broad range of data science techniques from the use of predictive analytics, analysing data using advanced quantitative methods, database management, linked data and/or complex datasets. This will give the RE a good understanding of data ethics from working on these projects.

The RE will then work with NHS National Services Scotland on:

  • mining datasets for assessing quality and building algorithms for predictive actionable insights
  • enhancing the statistical disclosure control process with algorithms for minimising the risks of revealing identifiable data.

The RE will also get an opportunity to work on projects with other parts of the Scottish Government and the NHS on other data science related projects during their studies.

We would expect a successful applicant to have a strong background in Statistics, Computer Science or a related discipline, with good programming and systems skills.


The projects that the RE will work on during their studies will investigate and propose unique solutions within key policy areas of the Scottish Government and the NHS, with the aim of providing tangible real-world improvements to the value of public spending and policy making.

Through the placement, the RE will have the opportunities to work with and present their work to industry experts, government and potentially international peers.