Vacancies for Research Engineers

If you are a Prospective Industry Sponsor and would like to list a vacancy on this page, please contact engd-admin-cs@st-andrews.ac.uk.

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

 


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.

Impact

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.


Ref: codeplay-2017-01

Large-Scale Data Processing using Heterogeneous Parallel Systems

Codeplay Software Ltd is an independent company that is based in Edinburgh. Codeplay is internationally recognized for expertise in Heterogeneous Systems, and has many years of experience in the development of Compilers, Runtimes, Debuggers, Test Systems, and other specialized tools.

Codeplay has delivered standards-compliant systems for some of the largest semiconductor companies in the world, focusing specifically on high-performance heterogeneous processor solutions for CPUs, GPUs, DSPs, FPGAs and other specialized imaging and vision processors. Working within The Khronos™ Group to define new open standards such as OpenCL™, SPIR™, SYCL™, and Vulkan®, and leading the creation of new System Runtime and Tools standards through the HSA Foundation, Codeplay has earned a reputation as one of the leaders in compute systems.

This project will investigate large-scale data processing using heterogeneous parallel processing systems. Self-driving autonomous vehicles and other AI applications, such as natural language processing, will generate massive amounts of data from a large number of sources (e.g. multiple cooperating vehicles in a city). The problem is to collate, analyse and process this data quickly and effectively. The project will study advanced algorithms that can effectively exploit new heterogeneous parallel processing systems for this purpose (comprising e.g. a mixture of CPUs, GPUs, DSPs and FPGAs). This will involve embedded processing, centralised processing (e.g. to collate/analyse data from multiple distinct sources) and/or peer-to-peer processing (for information sharing, to allow better use of computing resources, or to support e.g. flocking-style behaviours from multiple cooperating autonomous systems).

We would expect a successful applicant to have experience of:

  • Parallel Programming
  • Programming language implementation
  • Heterogeneous parallel systems (CPU, GPU, FPGAs) (optional, but an advantage)
  • Artificial intelligence (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 research team supervised by Uwe Dolinsky.