Tenure Track Fellow Grade 8

at  University of Liverpool

We are seeking an individual working to examine, extend and enhance the state-of-the-art in scalable Artificial Intelligence, Machine Learning and Data Science. We actively encourage individuals who are enthusiastic about investigating and engineering real-world solutions to pressing data-centric problems and to do so in a way that pulls on rigorous Bayesian statistics and scalable computational resources.
This tenure track lecturer position is a response to a growing need for ambitious academic staff to join a successful team of researchers developing and delivering a research portfolio currently valued at £25.1M. The individual will have a desire to work at the interface of novel data science, AI and machine learning that is useful for a wide-range of applications. The postholder will take a pivotal role in delivering the new £4.9M, System-P: an Office for Life Sciences (OLS) funded research programme that has enormous potential for transforming healthcare with novel data science as part of their support for a Health Data Action Accelerator in the Liverpool City Region.
You should be an enthusiastic, motivated and professional team player who will help deliver a research programme of local, national and international excellence. You should have a background in Engineering, Computational Statistics, Computer Science and/or a related Science field with experience in innovating effectively with multi-disciplinary teams and with external partners. You will have expertise, and evidence, in collaborating with non-academic organisations to solve real-world problems.
The University of Liverpool is a member of the UK’s Russell Group of leading universities. The University is committed to enhancing its international position of excellence as a research-intensive higher education institution. The School of Electrical Engineering Electronics and Computer Science is an Athena Swan Gold award holder and is committed to encouraging, developing and supporting individuals in their research and academic careers. The group itself offers a dynamic, diverse and inclusive working environment must be an integral part of our society, giving everyone the opportunity to participate and to benefit. Thus, we welcome applications from all sectors of the community. As part of our commitments to increase diversity and inclusivity within our school, we particularly welcome applications from women, people who identify as an ethnic minority, people with disabilities and people from LGBTQ+ communities, as they are currently under-represented in the Department of Electrical Engineering and Electronics.
A PhD in a discipline related to signal processing, data science, applied mathematics/statistics and/or engineering is required for this role.
Although the University has a hybrid working system, the expectation is that the successful applicant appointed to the role will work more than 50% on campus. Lectures and the majority of the research group meetings will take place face to face

Please refer the Job description for details