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. Responsibilities You will be responsible for the development of algorithms and software for data analysis take part in planning of experiments at synchrotrons actively participate in experiments Qualifications
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designing DNA, RNA and proteins to create nanoscale devices for applications in biotechnology and medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA
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medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA design. However, there is a great need to develop new software for the design of advanced RNA
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medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA design. However, there is a great need to develop new software for the design of advanced RNA
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, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand disease
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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through
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algorithms. This work will be evaluated through simulations and with physical drones in mock search-and-rescue missions. This position will involve close collaboration with the PhD student at SDU who is
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. The objective is to develop models and algorithms that capture spatial variability, uncertainty, and communication constraints, and to understand how these factors influence perception, adaptation, and
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning