30 machine-learning "https:" "https:" "https:" "https:" "The Open University" uni jobs at Lancaster University
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. Interested applicants are encouraged to review the information about the programme that is held online https://www.lancaster.ac.uk/health-and-medicine/dhr/dclinpsy/ and to arrange an informal conversation
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cross-institution grants. Further information about the Department is available at: http://www.psych.lancs.ac.uk Please upload a cover letter with your application. For this full-time post, we expect a
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revision techniques, and participating in teaching reviews and quality assurance processes. We are particularly looking for candidates who are passionate about creating an outstanding lab-based learning
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bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
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a PhD in mathematics or a related discipline and be able to demonstrate previous research experience in using mathematical machine learning and AI methods, or applied mathematics, to solve challenging
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bringing together observations and global atmospheric models using innovative statistical and machine-learning approaches. It will provide the first clear attribution of how different physical, chemical and
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life and prepare them for future study. You will work with participating students to monitor their progress and provide constructive feedback to maximise their learning so that they are able to achieve
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questions, please contact Noeleen Hammond Jones, Deputy Head of LUMS Careers (Work Related Learning) n.hammondjones@lancaster.ac.uk or Rory Daly, Head of LUMS Careers, r.daly@lancaster.ac.uk We welcome
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. • Excellent proficiency in Microsoft Office and a willingness to learn new systems. • A curious mindset and commitment to personal and team development. • A flexible, team-oriented approach. Lancaster
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that the postholder will be already familiar with automatic accent/dialect classification systems, but they will have demonstrable experience in learning, using and testing new methods and language technologies. In