20 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Bristol" Postdoctoral research jobs at Umeå University in Sweden
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development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department
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, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ Project
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has about 160 employees, about 30 of whom are postdoctoral researchers. For more information, visit: https://www2.umu.se/en/department-of-ecology-and-environmental-science/
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. Information about the group's research can be found on our website https://sixtlab.org/ For more information about the position contact Dr. Barbara Sixt, barbara.sixt@umu.se Additional information We look
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. Prof. Silvia Remeseiro, MTB / WCMM, via silvia.remeseiro@umu.se More information aobut the research in Remeseiro’s group is available through the following websites: https://www.umu.se/institutionen
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of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en
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of the agreement on fixed-term employment as a postdoctoral researcher. More information about the group’s research can be found on our websites: https://www.umu.se/forskning/grupper/covid-19/ https://www.umu.se/en
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support, among other benefits. See more information at: https://www.umu.se/en/department-of-computing-science/. You will research in collaboration with the Associate Professor Zoe Falomir. Interested
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anaerobic culturing techniques (e.g. anaerobic chamber, bioreactor) and analysis of 16S sequencing data. Furthermore, practical experience in working with mouse models is required. Other requirements
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in