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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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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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are particularly interested in individuals who have: Strong background at least two of the following areas: machine learning, natural language processing, large language models and multimodal processing Excellent
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in practical applications. We are particularly interested in individuals who have: Strong background at least two of the following areas: machine learning, natural language processing, large language
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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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. The programme is led by Dr Jutta Tobias Mortlock, in collaboration with UK government and military stakeholders. The role is ideal for a scientist-practitioner with a postgraduate degree in organisational
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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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military stakeholders. The role is ideal for a scientist-practitioner with a postgraduate degree in organisational psychology and a passion for applied, real-world impact. Background The post-holder will
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine