|£56,021 to £82,068 per annum
|5th December 2023
|8th January 2024
Teesside University is a dynamic and innovative institution, founded on more than 85 years of teaching and learning and currently serving a population of over 18,000 students.
We are now looking to appoint an outstanding individual as a Professor or Associate Professor in AI within our Interpretable and Beneficial Artificial Intelligence Research Group. The focus of the group covers three main themes – interpretable machine learning methods, computational health, and computational behavioural modelling. Importantly, the group strongly emphasizes interdisciplinary research collaboration among its members across the three themes.
Machine learning techniques are widespread in several applications, but they are often criticised because they lack domain knowledge, therefore limiting the trustworthiness and interpretability of any obtained model. An integrative approach that fully exploits the multimodal learning potential to integrate such models with experimental omics, imaging and clinical patient data is still lacking. The research group’s focus on computational health is on designing, implementing, and validating novel multimodal machine learning architectures that leverage omics data, imaging, metabolic models and clinical data to predict cell phenotypic traits (in biotechnology) or patient outcomes (in cancer biology). Moreover, the group has an existing stretch on computational and behavioural modelling. Our main research interests focus on game and decision-theoretic agent-based modelling, game theory, incentive design, opponent behavioural and mental modelling, brain-computer interface, and reasoning under uncertainty. We will continue with the fundamental investigation and expand towards multi-disciplinary research in conjunction with social science and health. We will investigate individuals and societal utilities within applications where individual human and human populations exhibit a large impact.
The group research is linked with two main University priority areas: (i) decarbonisation and sustainable energy solutions, through interpretable AI algorithms for route optimisation, and data-driven solutions for reducing CO2 emissions; (ii) supporting machine learning-driven solutions in clinical practice, ranging from prognostic predictors to biomarker detections, with several ongoing projects with the NHS and the NHC. The group research also has strong links with research from other schools and centres for example population dynamics study and incentive/behavioural modelling. We have collaborated closely with researchers from psychology and social sciences.
This is a crucially important role for us, and we are looking for candidates with the drive, enthusiasm, and vision to help us realise our aspirations in AI research. You will have experience of previous research towards design and implementation of AI frameworks as well as proven ability to work across disciplinary boundaries and build our interdisciplinary disciplinary research agenda. With excellent partnership working skills, you will have experience of working with industry and stakeholders to drive academic and industry collaboration and a track record of innovation, knowledge transfer and research commercialisation.
Please be advised that due to the minimum salary thresholds imposed by the UKVI, this post will qualify for University sponsorship under the Skilled Worker visa route.
If you are shortlisted, your interview it will take place in person.
Please note: the University may ask you to participate in a number of selection activities as part of the recruitment process.
Job Reference: Z03740
Closing date: 08 January 2024
Interview date: 15 February 2024
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