33 evolution-"https:" "https:" "https:" "https:" "https:" "https:" ";" positions in Sweden
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evolutionary transitions, machine learning, and genomics to decode pollen evolution and unravel sexual selection mechanisms shared across kingdoms” led by Prof. Tanja Slotte in close collaboration
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Genetics (MEG) Lab led by Johannes Cairns at the Department of Experimental Medical Science, Faculty of Medicine, Lund University. The group studies microbial evolution, antimicrobial resistance and
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Department of Biological and Environmental Sciences, University of Gothenburg | Sweden | about 1 month ago
measures to mitigate and adapt to these changes. This position is particularly linked to the BECC grand challenges “Biodiversity under Global Change” and “Ecosystem Services under Global Change” ( https
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million SEK in total assets. Subject area Bioinformatics and Cancer Genetics Subject area description Somatic mutation accumulation and clonal evolution are central processes in cancer
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-generation sequencing methodologies). Locally, the research project is connected to the Linnaeus University Centre for Ecology and Evolution in Microbial model Systems (EEMiS) and the Strong Research
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internal structure and evolution of AI-enabled components themselves, including the design of retrainable pipelines, model-wrapping services, LLM prompting logic, data pre/post-processing components, and
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dynamics Develop machine learning potentials to predict SAM formation on solar cell absorber and battery electrode surfaces Understand the evolution of the electronic structure under realistic
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employees and approximately 450 million SEK in total assets. Subject area Bioinformatics and Cancer Genetics Subject area description Somatic mutation accumulation and clonal evolution are
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Ph.D. levels. Work description As a doctoral student in this position, you are expected to explore how AI agents support and transform the requirements elicitation and evolution process (AI4RE) and how
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, the research project is connected to the Linnaeus University Centre for Ecology and Evolution in Microbial model Systems (EEMiS) and the Strong Research Environment ECOCHANGE that comprise expertise