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use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across the different organelles. Another approach is to use Monte Carlo
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interests, the project can take several directions. One option is to use Systems Biology methods to formulate a set of ordinary differential equations describing how genes regulate each other across
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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must have a PhD or equivalent Strong background in biomedical science or a related field Practical experience and scientific expertise in biomedical methods such as ELISA and immunohistochemistry, as
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experience working with deep learning methods for biomedical applications. Academic and Project Excellence: Evidence of high-quality research work, as demonstrated by academic grades, the merit of prior degree
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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of the student is of a person fully committed to forest economics research with foundational training in research methods. The candidate will be responsible for: integrating economics and natural resource
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combination of different methods such as population genetics, analyses of fungal environmental DNA and soil spore banks in soil to find out about the life histories of ectomycorrhizal fungi in general, and
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, part of the Wallenberg Initiatives in Forest Research (https://www.slu.se/WIFORCE/en ), was created. We are looking for an industry/collaboration-based PhD student in remote sensing to develop methods
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about Automated Reasoning'. From a fundamental research perspective, this relates to the automation of meta-reasoning pertaining to general-purpose reasoning methods. Here, the intended focus is on