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approaches which range from local micro-histories to large-scale quantitative analysis. We particularly value conversation between scholars of different periods and places, with different approaches. We also
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for the study of the history of the world. We are an intellectual home for scholars of every region of the world, who use approaches which range from local micro-histories to large-scale quantitative
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considered. The successful candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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colleagues. We put special emphasis on a flexible and cooperative working environment. Social interactions help facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role
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facilities such as microscopy, SEM, cavitation erosion and fatigue testing, micro/nano-indentation etc. is required. In addition, handling and processing of large data sets, knowledge of data acquisition
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at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
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at command line and BASH scripting Experience working with large scale, complex datasets and data wrangling skills Strong publication record and familiarity with the existing literature and research in
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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale genomic data analysis. You