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, molecular techniques and bioinformatics analysis is desirable. Experience in data analysis is advantageous. The applicant must be willing to travel for a 2-3 month research stay to learn new skills
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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the field of mechanical properties of glasses. The brittleness and low fracture toughness of various glass materials, including oxide and metal-organic framework glasses, remains to be their main disadvantage
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developing methods at the intersection of artificial intelligence and statistical genetics, with an emphasis on integrative analysis of multi-modal biomedical data. Expertise in Bayesian modelling, graphical
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strong Danish or Nordic element. The applicant therefore must be fluent in English as well as in Danish, and hold a Danish law degree. Ideally, the applicant must have undertaken previous study/research in
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of study is energy planning in general and focus is on technical and geographical aspects, such as energy system analysis, and economic and institutional aspects, such as feasibility studies and public
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neural networks are large black boxes, we need both automatic methods to analyze such systems and human-interpretable certificates of the analysis results. We will devise automatic and sound methods
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exploit such biomass when scaled up and integrated into an industrial setting. This analysis requires the combined application of qualitative and quantitative approaches to identify and describe future
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of the AI:EcoNet Lab. Requirements: Master’s degree in biology with a strong interest in data science Strong background in ecology and/or biogeography Experience with ecological networks, geospatial analysis and
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for managing End-of-Life (EOL) products, decision-making models for recovering, refurbishing, and reusing components from returned products, creating product and component traceability, effective disassembly