Senior ML Research Software Engineer (ICCS) (Fixed Term)

In the face of the present climate crisis, there is a pressing need for skilled software engineers to aid climate scientists in delivering a new generation of climate models. The Institute of Computing for Climate Science (ICCS) is a multi-disciplinary institute that has been established to develop and deploy machine learning (ML) and computational tools to advance the understanding of climate systems and inform decision-making for both climate change prediction and mitigation.

A core part of the Institute is our team of Research Software Engineers (RSEs) who reside in Research Computing Services. ICCS RSEs work closely with several international teams of climate scientists, including the Schmidt Sciences’ Virtual Earth Systems Research Institute, to develop and improve climate modelling tools and work with other members of ICCS to identify and implement projects which can have a wider impact.

We seek to appoint a Senior ML RSE for our RSE team. This position provides a unique opportunity to be involved in research projects directly connected to climate science, and broader research into supporting climate science through computer science, software engineering, and data science. The post also includes funding to support travel to conferences and for training activities to support career development.

Essential requirements for the role include:

• An advanced (M.Sc., Ph.D. or equivalent) degree in a STEM discipline or relevant experience.
• Experience in leading on the development of software, in particular in terms of using machine learning in modelling and simulation.
• Ability to guide scientists in software engineering and ML best practices and help to implement these within teams.
• Experience in planning and delegation in a project management environment.
• Proficient in one or more programming languages such as Fortran, C++, C, Python
• Excellent communication and problem solving skills.
• Experience in software development and related productivity tools (e.g., Git/GitHub, JIRA).
• Ability to engage productively, with people of different backgrounds, nationalities and skill sets.

A core part of the role will involve assessing the suitability of using ML tools in numerical simulations and developing ML solutions to optimise model performance. The post holder will also engage with stakeholders to communicate ethical considerations on AI and data.

This is a fixed term position. The funds for this position are available until 31 December 2028 in the first instance.

The University is supportive of hybrid working. This role allows the post holder to be office based or to work in a hybrid way.

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 the ‘Apply’ button above.

Queries should be directed to recruitment@uis.cam.ac.uk in the first instance quoting reference VC50606.

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.

£47,389 to £59,966 per annum

• An advanced (M.Sc., Ph.D. or equivalent) degree in a STEM discipline or relevant experience.
• Experience in leading on the development of software, in particular in terms of using machine learning in modelling and simulation.
• Ability to guide scientists in software engineering and ML best practices and help to implement these within teams.
• Experience in planning and delegation in a project management environment.
• Proficient in one or more programming languages such as Fortran, C++, C, Python
• Excellent communication and problem solving skills.
• Experience in software development and related productivity tools (e.g., Git/GitHub, JIRA).
• Ability to engage productively, with people of different backgrounds, nationalities and skill sets.

A core part of the role will involve assessing the suitability of using ML tools in numerical simulations and developing ML solutions to optimise model performance. The post holder will also engage with stakeholders to communicate ethical considerations on AI and data.