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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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for epidemiology with some coding of simulations. Tentative start date: February 2026. This work will contribute towards the understanding of disease progression and building reinforcement learning frameworks
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validated on a wastewater recycling pilot plant. Suitable methods for process analysis and characterization will be extended and the chemical-physical relationships will be studied using molecular and
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research outcomes will set you apart. A degree in Chemistry, Biochemistry, Pharmacology, or a related field (or equivalent experience). Demonstrated experience in molecular modelling, simulations, and