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in a group with a strong publication track record Work in a supportive, international environment just outside Copenhagen If you want to apply your skills in animal models and translational
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, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex
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academic career in a group with a strong publication track record Work in a supportive, international environment just outside Copenhagen If you want to apply your skills in animal models and translational
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(AUH), where the newly developed therapeutic oligonucleotides will be tested in preclinical models. Applicants must hold a PhD in chemistry and have documented experience in organic synthesis and nucleic
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bioinformatics and modeling of the complex microbial communities that shape our word. We are seeking a highly motivated post-doctoral researcher to develop scalable probabilistic machine learning models and
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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(e.g., Statistics, Mathematics, Physics). You will be passionate about science, hardworking, and excited to learn and improve skills in an outstanding research environment. You will be part of a
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new