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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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' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
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23.04.2024, Wissenschaftliches Personal We are offering one postdoc position to a highly motivated researcher with a background in geography and urban ecology with experience in modeling, GIS and
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Your Job: Synthesis and physicochemical characterization of energy materials or representative model systems Characterization of the dynamical and structural properties of energy materials with a
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, depending on the geographical and economic context. It will include a deep dive on the potential of Ukraine to become a green hydrogen hub, leveraging geo-spatial energy models run by project partners. As
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. For modeling, we use both public and proprietary clinical and research data and generate our own repository of digital pathology images. A further focus of our lab is the improvement of digital pathology
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will be tested and verified with applications from geodynamics. For more information consider the job description here . Tasks Tasks in the project include the efficient implementation of new models
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning