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engineering, and related disciplines, skills and experience in modelling and simulation, skills and experience in relevant software and programming environments, such as Matlab, Python, C++, UAS
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related to the project’s themes, and of automated text analysis, is a strong merit. Further merits include experience of programming and of working with large-scale social science data, as well as
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conduct computational research involving Python programming and high-throughput protein structure prediction using high-performance computing infrastructure. You will work closely with other members of
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quantitative analysis of transport, traffic-safety, mobility or comparable complex empirical data. experience of using programming languages or statistical computing environments, such as Python, R
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peptidomics, including analysis of complex datasets using specialized peptidomics tools. Experience in MS data analysis using software such as FragPipe and DIA-NN, as well as basic programming skills in
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practical experience in programming and data analysis in R. Good communication skills and extensive documented experience of supervision of degree projects. Good collaborative skills, initiative and
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analytical methods for the characterization of food, protein, or colloidal systems, knowledge and experience in statistical experimental design, modelling, programming, or multivariate data analysis
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following are also required: Good programming skills. Good ability to work independently and to formulate and tackle research problems. Good written and oral communication skills. Good ability to
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Lund Nano Lab. Transport and high-frequency microwave measurements, including programming of measurement scripts. Analysis of the measurement results to gain understanding on their operation and to
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analysis of images or volumes, e.g., in ImageJ, or Python. Experience in visualization software, e.g., Blender, DragonFly. Knowledgeable in programming, e.g., Python. Experience in developing user