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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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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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. 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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PhD fellowship/scholarship - Intercropping of cover crops and vegetables to mitigate nitrate leac...
the effect of species and management choices (e.g. sowing time) for complementary resource use and environmental and climate impact. The focus will be on cover crop and vegetable growth above- and belowground
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environmental applications of microsystems and the ability to interact with researchers in a very interdisciplinary environment. A high grade average and excellent English language skills are decisive to be
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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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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching
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. Their biodegradable or compostable nature helps to minimize environmental pollution, making them an eco-friendly choice for many applications. In this project we will explore protein-based biomaterials using bacterial
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an efficient AI foundational exploration of the molecular space. How can we bias the generative models towards desirable molecular properties How can we integrate generative AI models and different molecular