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opportunity to contribute to cutting-edge research aimed at understanding microbiome-driven mechanisms and developing novel strategies for disease prevention and treatment. You will collaborate with renowned
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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: (1) Aerospace Engineering and Mechanics, (2) Chemical and Biological Engineering, (3) Civil, Construction, and Environmental Engineering, (4) Computer Science, (5) Electrical and Computer Engineering
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of sustainable aluminium production! Your immediate leader will be the Head of Department. Your supervisor will be Prof. Andreas Erbe. About the project You will delve into the mechanisms of surface treatments
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for pharmaceutical and biotechnological use. The ideal candidate profile: Must-have: MSc degree in the fields of biophysics, soft matter physics, physical chemistry, computational chemistry, statistical mechanics