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of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models. Develop multistate sequence design algorithm for rational design of RNA switches. Develop database
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for a technician who will help with the quantitative analysis of a European travel survey and apply data science methodologies to predict travel behaviour in European cities as part of the EC funded
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project working to develop real-time vector-borne disease risk assessment in low resource areas. The individual will be directly responsible for the development of adaptive predictive models for nowcasting
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Develop and validate material models and performance predictions using simulation tools Integrate materials into injection moulding and extrusion processes through prototyping Collaborate with
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, as well as from industry. The successful candidate will work in the established collaboration between DSB and ICGI to develop multimodal deep learning models for predicting prostate cancer
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3); (iv) To estimate the environmental and human risks of using wastewater for irrigation (Activity 4) by applying risk assessment models; (v) Participate in disseminating project results
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so that we can improve the prediction, diagnosis, prevention and treatment of common diseases such as Alzheimer?s, cancer and cardiovascular disease. We take a computational approach focused on
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vegetation model. The new EEO-based vegetation model should then also be used to predict future transitions and biome shifts to ultimately answer the question to what extent C4 grasslands, savannahs and their
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://chiralnanomat.eu/ we offer two PhD positions: DC9 - Bio-Functionalized Chiral Nanocluster Modelling via Machine-Learning Methods DC10 - Predictive Modelling and Rational Design of Asymmetric Catalysis by Chiral
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areas: Artificial Intelligence/Machine Learning for Drug Discovery: Designing and applying machine learning models to identify new drug targets, predicting drug efficacy and toxicity, and optimizing small