49 machine-learning-"https:"-"https:"-"https:"-"Institut-Agro-Rennes-Angers" positions at Manchester Metropolitan University
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with experience or interest in learning and development, who are keen to contribute to our professional programmes, including those supporting qualification via the SQE. Successful candidates will be
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have access to a car. Why Join Us? This is an exciting opportunity to make a real difference to prospective students during a busy and impactful period. You'll join a friendly, supportive team committed
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educational engagement environment. This role includes national and reginal travel and frequent evening work. Is it an advantage to be able to drive and have access to a car. Why Join Us? This is an exciting
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to see applicants who are excited to teach in these areas and play a role in leading their development within the School. More generally, we are interested in recruiting colleagues with the knowledge and
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to understand teaching, learning and research priorities. Working collaboratively with academic colleagues you will ensure collections, learning support and academic liaison activity remains current, relevant and
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an outstanding teaching and learning experience for our students, whilst also building a research-rich culture to address some of the biggest challenges facing society today. Key to delivering this agenda is our
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learning and professional experience across the University. As part of the End User Compute (EUC) team, you will contribute to the engineering, management, security, and compliance of our multi‑platform
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and teaching performance across the Department. About the Role & Team We are looking for candidates with expertise in biotechnology, who will teach across our MSc Biotechnology, as well as microbiology
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Research in the department is distributed across five main themes: Machine Intelligence Data Science Smart Infrastructure & Cyber Security Human‐Centred Computing Computational Modelling The University is
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range of colleagues and customers in a busy environment? Are you comfortable learning new systems and adapting quickly when workloads change? If you can answer “yes” to these questions, we would love