14 machine-learning "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" "Mines Paris PSL" Postdoctoral positions at University of Liverpool in United Kingdom
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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and
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The opportunity The University of Liverpool is a key partner in a £14 million initiative ( https://tinyurl.com/yc5z768m ) to develop a sustainable, next-generation manufacturing facility, using
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transformation of society in western Europe (GREEKWEST)', which is funded by an ERC Starting Grant and hosted in the Department of Archaeology, Classics and Egyptology ( https://www.liverpool.ac.uk/archaeology
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transformation of society in western Europe (GREEKWEST)', which is funded by an ERC Starting Grant and hosted in the Department of Archaeology, Classics and Egyptology ( https://www.liverpool.ac.uk/archaeology
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transformation of society in western Europe (GREEKWEST)', which is funded by an ERC Starting Grant and hosted in the Department of Archaeology, Classics and Egyptology ( https://www.liverpool.ac.uk/archaeology
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experiments in gelatine (https://doi.org/10.5194/egusphere-egu25-9211). This model will be tested with analogue experiment results from the MAGMA Lab, run by other members of the project team. The second
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detection of comorbidity and multimorbidity patterns, https://aristoteles-horizon.eu / ) developing novel artificial intelligence (AI) powered tools to assess and manage multimorbidity in patients with atrial
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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m) to develop a sustainable, next-generation manufacturing facility, using
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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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. The project integrates synthetic organic chemistry, kinetic analysis, automation, and machine learning to establish next-generation mechanistic workflows for asymmetric organocatalysis. The project advances