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analysis for late-stage process chemistry The successful candidate will have the opportunity to design and build next-generation hardware modules that push the boundaries of automated chemistry. You will
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, work-up, and analysis for late-stage process chemistry (10.26434/chemrxiv-2025-bsfvz). You will have the opportunity to design and build next-generation hardware modules that push the boundaries
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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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mechanistic reach of the work. This is a basic science role embedded in a rich collaborative environment, supported by experimentalists across four universities and industry partners, with access to world-class
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novel plasma-disturbance sensing techniques. The role sits within the Department of Electrical Engineering and Electronics, part of the Faculty of Science and Engineering, which has a strong track record
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of the project we welcome applications from candidates who hold a PhD in a range of fields including Physics, Chemistry, Materials Science, Engineering. To apply for the position please follow the apply link and
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cellular biology approaches. - Analyse tumour samples from pre-clinical models and patient cohorts using high-dimensional platforms, including multiplex imaging, flow and mass cytometry
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is desirable, though candidates from non-glaciological/environmental science backgrounds will be considered and are actively encouraged to apply. You should have a PhD or equivalent applied experience
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nature of the role, prior experience in working with rheodialysis technique is an essential requirement. The position will be hosted in the Department of Materials, Design and Manufacturing Engineering at
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, particularly by providing expert advice in AI/ML-driven materials chemistry. This post will suit an ambitious individual motivated to produce step-change advances in new materials discovery and synthesis by