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stability, and computational efficiency. It is expected that the coding will be done with an open-source programming language. The field experiments have the aim of validating the modelling; they will involve
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conversion. The project partner at TUM will focus on the materials production, stability characterization and the catalytic activity tests aspect of the project. The work at DTU will focus on the materials
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general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of applicants will be made by Assistant Professor Raphael Ferreira together
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with methodologies such as AI-assisted evidence synthesis and quantitative health impact assessment and become part of an interdisciplinary research environment with strong links to DTU Compute and the
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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(120 ECTS) in chemical engineering, computer science, or a related discipline Some familiarity with ontologies, semantic data formats, knowledge graphs, and technologies such as OWL, RDF, SPARQL
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for sustainable production of food by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to do exactly that in a dynamic research environment. In the SOLARSPOON
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following qualifications: Programming skills and AI interest Data analytical skills and computer science focus Experiences with chemical analysis and pilot experiments is an advantage. Knowledge
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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. The position is an Alliance PhD partially funded by DTU and partially funded by Villum Fonden under the Villum Young Investigator program. The PhD project will investigate the molecular basis of enzyme-substrate