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Senior Exascale Software Engineer (Fixed Term)

University of Cambridge - University Information Services

Location: Cambridge, Hybrid
Salary: £45,585 to £57,696 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 7th May 2024
Closes: 31st May 2024
Job Ref: VC40379

Fixed-term: The funds for this post are available for 4 years in the first instance.

The University of Cambridge Open Zettascale Lab (COZL) is a research group whose aim is to evolve and utilise technologies that will make up the next generation of top-flight supercomputers. These state-of-the-art systems will help gain insights into humanity's global challenges, from the existential threat of climate change, through the devastating effects of diseases, to issues such as poverty, food insecurity and lack of healthcare services.

At the Cambridge Open Zettascale Lab, you will be part of a diverse team, working flexibly across the UK, to explore and exploit transformative technologies and support researchers at the forefront of computational science. This is a dynamic and rewarding environment, where exceptional people can gain early exposure to new technologies, work with important scientific codes and develop collaborations with leading international research groups. The Lab is housed within Research Computing Services a leading UK National Supercomputing Centre and home to Dawn, the fastest AI supercomputer in the UK, providing facilities and services to world-renowned scientists, clinicians and engineers across the UK and Europe.

As a Senior Exascale Software Engineer you will work in a small team alongside academics and external stakeholders to ensure the successful delivery of projects. The aim of the team is to develop and optimise advanced scientific applications for the next generation of supercomputing technologies. As a technical expert you will help domain specialists in the development of high-performance codes. These range from helping to develop internationally important simulation codes to producing new approaches to science problems using Machine Learning or Artificial Intelligence.

Candidates are expected to have:

  • A degree in a computational science, or equivalent relevant experience.
  • Experience writing and maintaining high-performance application code.
  • Experience in the key languages commonly used in scientific computing such as C, C++ (preferred), Fortran or Python.
  • Experience with at least one of the frameworks used to exploit large, modern parallel computers such as MPI, OpenMP or CUDA.
  • Some high-level knowledge of the hardware that forms a modern supercomputer (i.e. CPUs, XPUs and low-latency interconnects).
  • Proven ability to work effectively within a team and individually.
  • Experience of working in a scientific environment and/or providing support to researchers will be advantageous.
  • Skills in supervision and mentoring will be advantageous.

More information about the role is attached in the 'Further Particulars' document.

The University is supportive of hybrid working and we aim to enable as many staff as possible to work in a hybrid way if they wish and where their role allows.  This role allows the post holder to be office based, work in a hybrid way, or remotely with only minimal office attendance.

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 /or candidates from a BME background for this vacancy as they are currently under-represented at this level in our department.

To apply online for this vacancy and to view further information about the role, please click on the Apply button above.

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.

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
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