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12 Sep 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Chemistry » Analytical chemistry Chemistry » Physical chemistry Chemistry » Other Computer
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in
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) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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We are seeking a highly motivated candidate who has recently completed, or is close to completing, a PhD and has training in statistics, data processing, bioinformatics, or a related discipline, to
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cells, and their spatial organization within the tumor microenvironment. We use spatial transcriptomics and spatial proteomics, advanced image analysis, and computational approaches to investigate
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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application! Work assignments The project's contribution will lie at the intersection of random matrix theory and statistical inference theory, with applications in several fields of science. Special emphasis