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Department/Location: Department of Biochemistry, Central Cambridge PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based
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, release kinetics under biologically relevant triggers. The successful candidate will work at the interface of organic synthesis, chemical biology, and machine learning to guide linker design and optimise
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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knowledge with statistics, machine learning, Deep Learning and AI are an advantage • Good knowledge of the English language LanguagesENGLISH Research FieldEnvironmental science » Ecology Additional
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or Python) • Good knowledge of the English language • Experience with statistics, machine learning, Deep Learning and AI are an advantage • Familiarity with fundamental ecological concepts and experience in
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omics and big-data sets using statistical and machine learning approaches. The details on responsibilities, obligations and rights of the position see: https://www.osi.lv/en/vacancies/ Provisional start
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rearing insects. Moreover, you will extract plant chemical compounds in the lab and learn how to analyze them. The research will be conducted in close collaboration with the University of Neuchâtel. You
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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the Computer Engineering group. Curious to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab