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support the team within the EU- funded SkinEngineering project. SkinEngineering aims to enhance skin-bacteria for increasing human health. The recruited person will focus on: Microbial culturing. Support in
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physics-integrated machine learning models—to predict, analyze, engineer, and understand microbial community dynamics. Applications span precision medicine and built environment microbiomes, with a strong
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motivated Research Scientist to join the laboratory of Dr Lizbeth Sayavedra in the Food, Microbiome and Health programme at Quadram Institute Bioscience. The postholder will help investigate how microbial
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metabolic imbalances contribute to chronic diseases and ageing. Through our research we tackle major health challenges such as obesity and diabetes. For further information, please visit: https
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biology, microbiology, environmental science and environmental engineering as well as disease ecology. The Linnaeus University centre in Ecology and Evolution in Microbial Model Systems (EEMiS) in Kalmar
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science with microbial genomics and chemoinformatics. The research will be done in the research group of Erik Kristiansson (http://kristiansson-research.se ) at Mathematical Sciences, Chalmers University
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microbial hosts. Our interdisciplinary and international group offers a supportive, collaborative and dynamic working environment. About us The Department of Life Sciences conducts research, innovation, and
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crop science. The lab is jointly affiliated with the Departments of Plant, Soil and Microbial Sciences and Plant Biology, and the Plant Resilience Institute. Our mission is: To enhance sustainable crop
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to the identification of host and microbial metabolites and their pathways involved in metabolic diseases, including delineation of their genomic, metagenomic and environmental determinants. The objective is to develop a
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engineering, synthetic biology, and the development of improved microbial strains for applications in industrial bioprocesses, bioeconomy, and sustainability. Key Responsibilities Design and implement genetic