| Job Location | Egypt |
| Education | Not Mentioned |
| Salary | Not Mentioned |
| Industry | Other Business Support Services |
| Functional Area | Not Mentioned |
**Salary: 35,326 to 40,927 per annum pro rata Contract:35 hours per week until 31/08/2023**Location: Bay CampusTo deliver its sustainable top 30 ambition Swansea University needs a workforce with the differentiated skills necessary to ensure that it can deliver excellence in research and to be a powerhouse for the regional economy and internationally. Swansea University has been commissioned to conduct evaluations for the NHS Accelerated Access Collaborative. We are building a dedicated team to undertake critical evaluations of new AI technologies for health and care settings. Crucially, our work will fill key evidence gaps for relevant published evidence standards frameworks and accelerate local and national adoption of novel technologies. This role is an exciting opportunity to join the consortium team at Swansea University in the Department of Computer Science. You will provide specialist knowledge, experience, and capability for the benefit of the consortium and work with other consortium members (Technology-Enabled Care Cymru and Health Technology Wales) to conduct a wide-reaching evaluation of a novel Machine Learning or Artificial intelligence technology being developed and deployed within NHS settings. You will be responsible for support the capturing of data and analysing the performance of the software decision making in support the triaging of patients. Using this data, you will be expected to analyse this data using a range of different metrics including standard ML performance metrics, metrics that are robust to unbalanced data sets, range a of FairML metrics, and explainability methods. Finally, you will be able to produce publications and disseminate your findings within the consortium at internal meetings, with partners, and at public venues (e.g., conferences). Specific responsibilities: * Capturing performance data and evaluating Machine learning algorithms * Establishing an understanding of the algorithmic approaches used in learning * Applying evaluation techniques on black box algorithms for fairness and explainability * A postgraduate qualification and/or PHD in Computer Science/Data Science or equivalent * Evidence of active engagement, personal role, and contribution to writing and publishing research papers, particularly for refereed journals. * Evidence of the capacity for active engagement in designing research and writing, or contributing to writing, applications for external research funding. * Ability to demonstrate significant independence of focus and direction in research determining what, why, when and with whom to progress work. * Evidence of evaluation Machine learning and/or AI algorithm performance * A commitment to continuous professional development
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