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School and British Isles DBT Training to deliver a national, NHS England funded, distance-learning programme of PG Dip training in DBT. This post will provide outstanding opportunities to develop skills in
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are committed to maintaining a safe and secure environment for our students, staff, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant
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subject, including: biomedical engineering, sports science, physiology, medical science, data science. The candidate must have good data handling skills and have or be willing to learn computer programming
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Language Processing and Machine Learning are requirements of the role as well as considerable experience in the finance industry. There will also be opportunity to collaborate with external companies---experience
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learning, and leads on the University’s Access and Participation Plan (APP). A key focus of the Directorate is ensuring the University has a high quality and sustainable educational portfolio, which delivers
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partners in Thailand and Australia in a project funded by the British Council, and you will be responsible for investigating the latest developments in computer vision and Deep Learning to develop powerful
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School and British Isles DBT Training to deliver a national, NHS England funded, distance-learning programme of PG Dip training in DBT. This post will provide outstanding opportunities to develop skills in
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@bangor.ac.uk Closing date for applications: 22/06/2025 Committed To Equal Opportunities The Project The project is a study on the cognitive mechanisms underpinning foreign language learning in adults. The aim
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involve working with multiple staff across the UK who are delivering local projects and also with the central IMPACT team located at the University of Birmingham. Description of Duties Supporting monitoring
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enthusiasm for the topic will be expected, along with the ability and willingness to both learn and synthesise evidence and work with colleagues from various subject areas. Experience in longitudinal data