36 learning-"https:"-"https:"-"https:"-"https:"-"https:" positions at Lancaster University
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of opportunities to connect with colleagues and become part of our welcoming community. Learn more about our employee benefits on the Lancaster University Jobs website . Applications Please use your application
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research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs
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to develop novel AI approaches for automated behavioural monitoring from underwater video, contributing across computer vision, machine learning, edge AI and interpretable decision-support systems
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and climate adaptation worldwide. Your research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build
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professionals within the division and will acquire process, operational and general knowledge. This provides the perfect opportunity to identify how we can improve our processes and work more efficiently. You
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provision. We provide inspirational and high-quality learning environments that encourage academic excellence, promote partnerships, and respond to the changing expectations of our users. In
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, organisation and problem-solving skills enthusiasm for learning and working as part of a multidisciplinary team. You do not need experience in every area. You will be supported by knowledgeable colleagues
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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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two return flights. The accommodation is conveniently located near the teaching campus with amenities nearby. You will teach modules within the Design Interaction programme, which is a four-year
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to being user-focused, digitally driven, socially inclusive and innovative in our approach to service provision. We provide inspirational and high-quality learning environments that encourage academic