The University of Cambridge Open Exascale Lab (COEL) is an exciting new initiative to explore and exploit the next generation of advanced technologies which will form the world's fastest supercomputers. These state-of-the-art systems will allow us to understand the fundamental nature of the universe, design new materials, clean energy solutions, and to develop and deliver personalised medicine and data-driven healthcare.
The COEL is housed within Cambridge Research Computing Service a long standing and leading UK National Supercomputing Center, providing HPC services to world leading scientists, medics and engineers across the UK. We operate the UK's most powerful academic supercomputer, the UK fastest academic AI system, the UK's fastest data storage solution and the UK's first production 10 petaflop GPU/X86 heterogenous system. This is all managed by a highly innovative OpenStack Research Computing Software Environment via a software defined / DevOps methodology evolved for the cloud native world we live in today.
The COEL has several exciting opportunities for exceptional candidates to join a growing team within the lab.
The Principal Exascale Software Engineer will manage a small team of highly technical research software engineers on multiple projects to develop and optimise advanced scientific applications for the next generation of supercomputing technologies. The successful candidate will work with closely with the technical programme manager, key academic collaborators and external stakeholders to define and assure successful delivery of the projects. This successful candidate will have:
- A MSc or PhD degree in Computer Engineering, a computational science-based discipline or significant relevant experience.
- Experience writing and maintaining high-performance application code, and
- Significant experience of the key languages commonly used in scientific computing such as C, C++ (preferred), Fortran or Python.
- Significant experience with one or more of the main frameworks used to exploit large, modern parallel computers such as MPI, OpenMP, CUDA, OpenACC or PGAS is required.
Additionally, candidates should have demonstrable experience of managing highly technical teams and excellent communications skills, you will be confident in presenting the work of your team to a variety of external stakeholders and peers.
Experience or knowledge in the areas of machine learning and data science is highly desirable.
Further information is available on our website and in the attached further particulars document.
Fixed-term: The funds for this post are available for 2 years in the first instance.
Applications are welcome from internal candidates who would like to apply for the role on the basis of a secondment from their current role in the University.
We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.
We particularly welcome applications from women and candidates from a BME background for this vacancy as they are currently under-represented at this level in our institution.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Please upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
For any queries regarding this position, please contact Dr O.G Parchment via email firstname.lastname@example.org
As we have a number of available positions we will be reviewing applications and inviting suitable applicants for interview every 3-4 weeks.
If you are interested, we ask that you submit your application as soon as possible as we reserve the right to close these adverts at any time once we have received sufficient applications and/or made offers of employment.
Further information is available on our website https://www.exascale.hpc.cam.ac.uk/ and in the attached further particulars document.
Please quote reference VC27339 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.