Lecturer in Distributed Machine Learning and Digital Twins

University of Leicester

Job title:

Lecturer in Distributed Machine Learning and Digital Twins

Company:

University of Leicester

Job description

The University of Leicester invites applications for a Lecturer in Distributed Machine Learning and Digital Twins within the School of Computing and Mathematical Sciences. In this role, you will contribute to world-changing research and innovative education, with a focus on distributed and high-performance systems. Your research will align with areas such as advanced distributed machine learning algorithms, scalable AI systems, and trust-aware digital twin platforms. This position also offers the opportunity to engage in interdisciplinary projects, including partnerships in life sciences, space technology, and climate science.You will lead research projects, publish impactful work, and secure funding for new initiatives while delivering high-quality teaching at undergraduate and postgraduate levels.You will join the eponymous group led by Prof. Ashiq Anjum. The group has been successful in obtaining funding for a number of projects based on self-learning digital twins, and plans to expand into quantum systems and quantum machine learning. Ability to strengthen any of these areas would be particularly welcome.The School has research links with Space Park Leicester, the College of Life Sciences (including the Leicester Institute for Precision Health and the Leicester NIHR Biomedical Research Centre), and Institute for Environmental Futures at the University of Leicester and aims to strengthen and deepen these research links. The School is a founding member of the College of Science and Engineering’s Centre for AI, Data Analytics and Modelling (AIDAM), and has ambitions to lead a future UoL research institute in Data Science.About youWe are looking for a passionate and forward-thinking academic with a PhD or equivalent in computer science or a closely related field. You should have expertise in distributed machine learning algorithms, quantum systems, and high-performance AI, with a proven track record of publishing world-leading research. Experience embedding machine learning in distributed cyber-physical systems or developing digital twins that integrate real-world constraints is highly desirable.You will be able to inspire students and delivering innovative teaching across core areas such as distributed computing, programming languages, and software engineering. You will have demonstrated the ability to secure external funding and engage with interdisciplinary research. Your interpersonal and organisational skills will support your success as a collaborative team member.Additional informationFor informal enquiries, please contact Professor Ashiq Anjum ( , head of DHPS group) or Professor Rajeev Raman ( , Director of Computing Research).We anticipate that interviews will take place in February 2025.Applications for job share will be considered.The University of Leicester has been changing the world, and changing people’s lives, for 100 years. When you join us, you’ll become part of a community of , which includes not only our staff and our current students but also thousands of Leicester graduates around the world.As a diverse and forward-thinking employer, we embed the principles of equity, diversity and inclusion into everything we do. That includes not just our core missions of teaching and research, but also our support for staff, students and our local community through our values of Inspiring, Impactful and Inclusive.We’re committed to the wellbeing of all our staff and to the sustainability of our environment, on our campus and beyond. We offer a competitive salary package, excellent pension scheme and a generous annual leave allowance, along with opportunities to develop your career in a supportive and collaborative environment.

Expected salary

£45163 – 55295 per year

Location

Leicester

Job date

Sun, 01 Dec 2024 01:11:21 GMT

To help us track our recruitment effort, please indicate in your email/cover letter where (vacanciesin.eu) you saw this job posting.

To apply for this job please visit jobviewtrack.com.

Job Location