Connecting research to applications, helping create usable and sustainable tools, practices and systems.
Researchers and practitioners face a common need for high quality tools, practices, methodologies, platforms and systems.
Many domains can benefit from the deployment of cutting-edge algorithms and approaches, but these cannot be effectively applied unless realised as usable software libraries, reproducible analyses and workflows, or high performance computational environments.
The Research Engineering team contributes skills in research software engineering and data science in support of other programmes, as well as to its own projects. This model of working ensures that the tools they develop are useful and applicable to a wider range of areas. The team supports professional delivery of impactful research across the Turing's programmes, as well as its own research interests.
Research Engineering's work is aligned with the Institute's main research challenges which aim to represent areas in which AI and data science can have a game-changing impact for science, society, and the economy. For each, a Challenge Lead helps to coordinate our partnership with the corresponding research programme.
Turing researchers and students looking for help from Research Engineering should email the relevant Challenge Lead.
The team is offering a course on research software engineering with Python for Turing Doctoral Students and a limited number of Turing researchers.
Impact Story - Making simulations simpler
Members of the team, in collaboration with the Turing's programme in Data-centric engineering, and partners at Imperial College and UCL, have developed a user interface (UI) that aims to make the simulation process more user-friendly, for both academic and industrial communities. Read the full Impact Story here, and see the related project page here.