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will contribute towards the Continuing Professional Development of relevant practitioners, as well as provide key learning resources for interested parties. The successful applicant will be expected
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colleagues on relevant oenology research, publish high‑quality outputs, and support undergraduate and postgraduate learning. Some tasks of the role include: Conducting collaborative research in agreed wine
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. Develop AI and machine learning models for recycling process prediction and decision support, such as forecasting metal recovery, impurity levels, energy use, and emissions. Develop optimization and control
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Centre for Lifelong Learning and Individualised Cognition CLIC is a research collaboration between the University of Cambridge and Nanyang Technological University (NTU) and hosted by the Cambridge
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Requisition Id 16254 Overview: Do you have a passion for applying AI methods for accelerating scientific discoveries and an ability to think outside of the box in a collaborative and open
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with customers and collaborators in A*STAR and NTU, as well as collaborators in the UK and China. Key Competencies: A self-directed worker who believes in continuous learning and development Proficient
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learning, to help solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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collaborative learning, you identify critical friction zones and promising ways forward, effectively accelerating the uptake of scientific innovations in real-world applications. Key Responsibilities: Collaborate
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publications and presentations. They will also assist in the preparation of project reports and collaborate with interdisciplinary teams. Duties: The appointee will be involved in the full lifecycle of research