55 parallel-processing-bioinformatics-"Multiple" positions at University of Bergen in Norway
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in shaping the future? PhD position There is a vacancy for a PhD Research Fellow in Snow Processes in Mountainous Regions at the Geophysical Institute and the Bjerknes Centre for Climate Research
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1st October 2025 Languages English English Norsk Nynorsk English PhD Research Fellow on Snow Processes on Coastal Ice Caps Apply for this job See advertisement UiB - Knowledge that shapes society
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1st October 2025 Languages English English Norsk Nynorsk English PhD Research Fellow in Snow Processes in Mountainous Regions Apply for this job See advertisement UiB - Knowledge that shapes society
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computer science, systems engineering, cybernetics, applied mathematics or another relevant degree at the same level, and applicants must also have a specialization in signal processing, bioinformatics, simulation
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specialization in signal processing, bioinformatics, simulation/visualization, or dynamic systems, or have the doctoral thesis submitted prior to the application deadline. It is a condition of employment that
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objectives are to (i) improve process understanding of variation and context-dependencies in biodiversity change, (ii) assess and compare the impacts of multiple global change drivers, and (iii) explore
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-high-resolution analyses of lake sediments to reconstruct glacier dynamics across multiple regions. The findings will contribute to understanding future glacier changes in Scandinavia and globally and
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encourage men to apply. If multiple applicants have approximately equivalent qualifications, the rules pertaining to moderate gender quotas shall apply. Information about applicants may be made public even if
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, ethnicity, religion, worldview, disability, sexual orientation, gender identity, gender expression, and age. We encourage men to apply. If multiple applicants have approximately equivalent qualifications
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will investigate the patterns, drivers, and consequences of vegetation change in mountainous regions. The overall objectives are to (i) improve process understanding of variation and context-dependencies