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(s) will join a new research group developing statistical methodology for the social and behavioural sciences, where data are increasingly large-scale and high-dimensional, yet often noisy and subject
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pave the way for science, creativity and development. Therefore, we welcome applications from people with diverse backgrounds and perspectives. Where to apply Website https://web103.reachmee.com/ext/I017
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relevant scientific questions and collaborate with other researchers. As postdoctoral appointments are career-developing positions for junior researchers, we are primarily looking for candidates with a
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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to develop cultivation methods for traditional pea varieties which have desirable traits in cropping (e.g. weed suppression and productivity) and as food source (nutrient content, taste, etc.) but
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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resilience. The major limitation in this debate is however the lack of comprehensive empirical data which is a prerequisite for developing well-constrained strategies to benefit biodiversity and its ecosystem
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at: www.ftf.lth.se , www.nano.lu.se , https://kaw.wallenberg.org/en/research/semiconductor-bandgap-key-future-green-electronics, https://c3nit.se/ Subject description The purpose of this project is to develop a data
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(NC). In the project, we aim to establish a reliable analysis package for nitrocellulose. Your role is to develop and validate methods for the key properties of NC – including degree of substitution
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orchestration, while leveraging new technologies such as integrated sensing and communication (ISAC). These initiatives bring together leading academic, industrial, and public-sector partners to develop