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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
), statistical analysis, modelling, and mapping Highly motivated and eager to work in an interdisciplinary marine research context Excellent communication and teamwork skills, with the ability to collaborate
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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
statistics and the ability to apply quantitative analysis to ecological data A strong background in programming (preferably in R), including data manipulation, statistical analysis, and spatial modelling and
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transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”. For section 4.7 “Earth Surface Process Modelling” (department
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motivated and has the ability to work independently as well as in a collaborative environment. Experience working with mouse models is a plus. The qualified candidate has the opportunity to be supported by a
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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
of the adverse effects of the space environment utilizing satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate
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environment using models and data assimilation. We study the fundamental processes in the near-Earth environment and focus on understanding fundamental processes responsible for the evolution of space radiation
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in January 2025. The overarching goal is to identify the key factors controlling microbe-mediated carbon storage in the ocean, with a focus on using model microbial systems in the lab. We specialize in
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transcriptomics and genomics datasets. The goal is to identify molecular and spatial signatures of disease progression both in human samples and in experimental models of diabetes. Qualifications: PhD in
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on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from
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pharmacological questions in large populations. The translational pharmacology group aims to understand variability in drug toxicity, drug metabolism and drug transport. Examples of this include cell-based models