Lecturer in Machine Learning

The School of Electronics, Electrical Engineering & Computer Science at Queen’s University Belfast (QUB), is seeking to appoint a Lecturer in Machine Learning.

The successful applicant will contribute to our ambitious research agenda and help to establish QUB as an international leader in Machine Learning research and the application of this research to real-world challenges.

The post holder is expected to develop an independent program of world class research and innovation, engaging with the transformative innovation programs being delivered by QUB as part of the Belfast Region City Deal (BRCD) as appropriate. They will enhance an excellent student experience via research-led teaching and assessment and will also contribute to administration of the School and the University, to citizenship in their research communities, and to outreach activities that showcase research to the wider public.

About the person:

The successful candidate must have, and your application should clearly demonstrate that you meet, the following criteria:

• Have a PhD in Computer Science, Computer Engineering, Electronic Engineering (or related discipline).
• Demonstrate a strong record (commensurate with career stage) of conducting and publishing high quality research in Machine Learning (ML), including but not limited to: optimisation, explainable ML, distributed and federated learning, causal ML, graph ML, self-supervised learning, and ML for science, finance, cybersecurity and communication.
• Evidence of independent contribution to research projects and outputs and potential to establish an independent and sustainable research program.
• Evidence of contribution to national and international collaborations.
• Evidence of teaching experience including but not limited to undergraduate and postgraduate level teaching, assessment and/or industrial training activities.

To be successful at shortlisting stage, please ensure you clearly evidence in your application how you meet the essential and, where applicable, desirable criteria listed in the Candidate Information document linked on our website.

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