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, the CAPeX approach to finding new electrocatalytic materials for energy conversion reactions uses state-of-the-art machine learning techniques, but experimental feedback is needed to improve the models and
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
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characterization of glycoside hydrolases, and a postdoc working on computational modelling of the same enzymes. The PhD focuses on ligand-observed NMR analyses and other relevant methods to provide insight
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circular, economically viable future for packaging. Through SSbD assessment in collaboration with the consortium, experimental work and risk modeling, you will help uncover the hotspots in the production
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. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with correspondingly skilled
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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(ORR), oxygen evolution reaction (OER), and carbon dioxide (CO₂) reduction. Collaborating with theoretical research groups to guide the design of active site structures through computational modelling
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, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or cheminformatics are advantages. The candidate must be able to work independently, but also participate in
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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching