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learning methods for protein design Design of enzymes using computational models Identification and optimization of plastic-degrading enzymes Experimental expression, purification, and characterization
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: Development and application of AI and machine learning methods for protein design Design of enzymes using computational models Identification and optimization of plastic-degrading enzymes Experimental
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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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methods have limited ability to identify patients at intermediate risk, despite this group accounting for a substantial proportion of disease burden. The project focuses on early identification
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writing of manuscripts and publication. Identification of knowledge gaps through independent work and literature review, and presentation of strategies to address these gaps. Independent development
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. Please note that identification must be presented at the interview. Contact persons Deputy Head of Department: Andreas Svensson (andreas.svensson@lnu.se), +46 (0)480-447319 Research leader: Daiana de
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identification and mechanistic studies, in collaboration with researchers at Uppsala University Evaluation of promising drug candidates Mechanistic studies of antibody-mediated inflammation The position combines
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, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification -- one notable example is given by Gaussian process
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systems. However, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification -- one notable example is given by
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design, MS analysis, identification of reaction products, quantification and subsequent optimization to generate the chemicals, fuels and materials of the future. Furthermore, knowledge of important