- Provide researchers with specialised training in AI techniques, equipping them with the skills they need to use machine learning and AI to power their research.
- Pursue an ambitious research agenda that applies machine learning to the scientific challenges of the 21st century.
- Build a community of researchers working at the interface of machine learning and the sciences to share knowledge and experiences that help advance the use of machine learning in the sciences.
- Guide scientists in software engineering best practices and help to implement these within the teams.
- Work closely with scientists to help scope, gather requirements for, and design their applications.
- Develop software in tandem with climate science teams, including extending existing code.
- Identify and implement opportunities to improve the performance, sustainability, and quality of the applications.
- Demonstrate a customer service orientation, giving priority to high customer satisfaction.
- Interface with the Institute's research team to help gather problems that then feed into the research programme of the institute.
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Machine Learning Research Software Engineer - Cambridge, United Kingdom - University of Cambridge, Institute of Astronomy
Description
Fixed-term: The funds for this post are available for 5 years in the first instance.
Software development is a highly valuable resource that includes modelling, simulation and data-analysis. Generating well-designed software will in turn increase the scope, productivity, reliability, replicability and therefore openness of research. In pursuit of these goals, we are seeking an experienced Research Software Engineer to lead the development of our software culture.
The Research Software Engineer will lead software development activities that facilitate the application of machine learning for scientific discovery. By providing software engineering support, advising on the development of research projects and delivering training and mentoring to researchers, the role-holder will be responsible for creating an environment that embeds good practice in scientific programming in research. They will be an evangelist for the role of software engineering in machine learning research. In particular, they will:
The University is supportive of hybrid working, where some work is undertaken on University premises and some in a remote UK-based working environment. This role requires a minimum of 60% of contracted full-time hours on University of Cambridge premises per week. Conversations about flexible working are encouraged at the University of Cambridge. Please feel free to discuss flexibility prior to applying (using the contact information below) or at interview if your application is successful.
Click the 'Apply' link to register an account with our recruitment system (if you have not already) and apply online.
Please indicate the contact details of three professional referees on the online application form and upload a full curriculum vitae (CV), list of publications, and a research/technical experience statement (this research/technical experience statement being three pages max in 11pt font).
The application deadline is 23:59 BST on Sunday 16th June 2024.
Referees will be requested to provide references by the same date. Where permission is given by the applicant, references will be requested prior to the vacancy closing. Applicants are asked to inform their referees that they will receive a reference request communication including a link to upload a reference to the University of Cambridge recruitment system by the application closing date.
Applications will be reviewed after the closing date and interviews will take place the week-commencing 1st July 2024.
The start date of the appointment is negotiable on or before October 2024.
Please quote reference LG40978 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 of Cambridge thrives on the diversity of its staff and students. Applications from underrepresented groups are particularly welcome. We have an active Equality and Diversity Committee which continually works to further the aims of the Athena SWAN charter. The University has a number of family-friendly policies and initiatives, including a returning-carer scheme, childcare costs support, university workplace nurseries, university holiday play-schemes, and a shared parental-leave policy.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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