Software Developer

Hours: Part time considered up to a maximum of 50% FTE

Contract Type: fixed term until 31 December 2025

Expected Interview date: 25 February 2025

Expected start date: March 2025

About the role

As part of our efforts to advance AI in wearable technologies, we are looking for a software developer to complement the team. The applicant will have strong joint engineering and scientific background, with a demonstrated expertise in applied AI and applied machine learning, a solid understanding of the challenges and approaches to managing terabyte-sized machine learning datasets, and an appreciation of the needs of the scientific community in relation to establishing recognised AI benchmarks.

The applicant will have expertise in a variety of technologies which will enable this, including strong coding skills (e.g. Python, Matlab, C, Tensorflow, Pytorch); solid expertise in the deployment and management of computing infrastructures (Linux; Docker, Kubernetes, Puppetteer; AWS, Git, etc), web-based systems (CMS; HTML, JavaScript), experience in the design of high-performance code (e.g. OpenCL, CUDA).

About you

The applicant will have strong organisational skills and will be able to work with a high degree of autonomy and self-motivation in a large, versatile, European research project, taking own initiatives, be creative, ambitious and contributing to enhancing the reputation of the University of Sussex in AI. The applicant will participate in EU project meetings (online or in EU countries if travel restrictions allow for this), and will be expected to initiate and lead activities related to large-scale AI datasets and AI/ML challenges.

About our Division/School

You will work directly with Prof. Daniel Roggen in the Wearable Technologies Lab, part of CROSS-TECH in the Department of Engineering. The Wearable Technologies Lab at the University of Sussex has a major research focus on computational behaviour analytics: the science advancing sensor technologies and AI to recognise and eventually understand human activities and behaviour, for a wide range of applications with high societal value. The Centre has established several large scale machine learning datasets (e.g. the SHL Locomotion/Transportation Dataset; the Opportunity dataset of activities of daily living; the Skoda dataset of manufacturing activities) and has organised several machine learning challenges over the years (e.g. the Opportunity Challenge in 2011 and the SHL Challenge in 2018, 2019, 2020, 2023  and 2024).

Why work here

Find out more about our reward and benefits package.

Find out about our equality, diversity and inclusion

Further Key Information

Please contact Daniel Roggen (d.roggen@sussex.ac.uk) for informal enquiries.

For full details and how to apply please click the 'Apply' button, above.

The University is committed to equality and valuing diversity, and applications are particularly welcomed from women and black and minority ethnic candidates, who are under-represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex.

The University of Sussex values the diversity of its staff and students, and we welcome applicants from all backgrounds.

The University requires that work undertaken for the University is performed in the UK. 

Visa Sponsorship Queries: This role may be eligible for sponsorship.

Please consult our Skilled Worker Visa information page  for further information about Visa Sponsorship.

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