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, flexible and adaptable distributed system of systems. Example of specific problems are: -Information interoperability supported by ontologies. -Unified data models for operational environmental impact -SOA
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in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
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found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production and in the interaction between these areas. The research covers
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health
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interfaces and driver modelling Implementation of control algorithms in mechatronic systems Experimental design and statistical methods Vehicle testing and test methods involving human test subjects What you
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be paid to the following experiences: -Experience in sampling and analyses of building materials -Experience in Life Cycle Analysis in construction sector. -Experience in building information modeling
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Associate Professor Åsa Johansson at Uppsala University, Department of Immunology, Genetics and Pathology. The group focuses on identifying risk factors for common diseases and developing models for risk
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, image processing, biological modelling and biostatistics. Experience working with (or knowledge in) plant cell walls, phytohormones signalling, mechanobiology, plant growth and development. Experience
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modeling of magnetic materials using first-principles methods. Good knowledge of programming is required. Meritorious experience for the position is demonstrated knowledge of Git, Python, Bash and VASP. Good