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                practice or other forms of appointment/assignment relevant to the subject area. The doctoral degree should be within Analysis of PDEs or similar. A strong mathematical background in the analysis of PDEs and 
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                the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software 
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                . The core work responsibilities include compilation and analysis of metagenomic data in clinical translational projects. The application deadline is 9 November. Description of the project The work will be 
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                6 Sep 2025 Job Information Organisation/Company Linnaeus University Research Field Mathematics » Mathematical analysis Researcher Profile Recognised Researcher (R2) Country Sweden Application 
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                . Both are part of the Department of Mathematics and Computer Science, which provides a vibrant, inspiring, collaborative, and highly international environment for your work. Due to the postdoctoral 
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                agendas, and social visions, as well as their impact on human rights, democracy, and civil society. You will be part of a committed and interdisciplinary team with a strong research profile and close 
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                quantitative genetics Expertise in the use of quantitative genetic analyses and generalised linear mixed-effects models, and ideally also in the use of some mathematical models (e.g. Integral Projection Models 
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                of hybrid-electric aero-engine performance and environmental impact will be a key focus. The project also includes preliminary system design and mission analysis. A large part of the work will be conducted 
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                performance and environmental impact will be a key focus. The project also includes preliminary system design and mission analysis. A large part of the work will be conducted at – or in close collaboration with 
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                presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods