45 genetic-algorithm-computer Postdoctoral positions at Technical University of Denmark in Denmark
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-disciplinary involving algorithmics, stochastic optimization, multi-criteria decision making, and data science. As part of the project, you will implement and test algorithms and further develop your skills in
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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Job Description If you are excited by the challenge of understanding extinction through cutting-edge computational approaches, this postdoc offers a unique opportunity. You will help develop a
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for leading the following efforts: Design, build, and characterize engineered yeast strains and synthetic biology systems (e.g., DNA design, cloning, PCR, plasmid building, genetic engineering, mutagenesis
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genetic manipulation of (non-model) bacteria Demonstrated ability to work independently, take initiative, and drive projects forward Well-organized, reliable, and motivated to help establish a positive
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Job Description These days, the inner workings of molecules and materials can be probed and modelled by advanced simulation tools on modern computer architectures. However, the routine applications
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DTU Bioengineering aiming to design novel Carbohydrate-Active enZymes (CAZymes) de novo (from scratch). Using state-of-the-art AI-based protein design tools, the project integrates computational design
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of magnesium-based binders in different environments, with particular interest in carbonation mechanisms. You will gain hands-on experience with advanced equipment and computational modelling tools to analyse
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computational and experimental techniques. Play an active role in education and outreach in protein design, including contributions to teaching and mentoring activities. You must have a PhD in a relevant field
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the molecular-genetic foundation for how microbial physiology is shaped by fermentation and formulation processes—and how those processes, in turn, affect the application efficacy of microbial products