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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
experience with nonequilibrium statistical physics and a strong interest in active matter physics; Ability and desire to work in an international team on inter-disciplinary research topics; Good command
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and workshops • 30 days of recreational leave • Becoming part of a dynamic young research group that is deeply committed to your professional development and growth as a scientist • Excellent
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). The institute also maintains locations in Dedelow and Paulinenaue. The PostDoc will work within the Resource-Efficient Cropping Systems group in the CropCat project on upscaling minor crops with institutional
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. The successful candidate will focus on molecular seed quality assessment using high-throughput metabolomics (LC MS/MS) and proteomics to support the breeding of climate-resilient crops. You will work with a
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in the nearest future a doctoral degree in the above-mentioned fields; are curious, highly motivated and self-driven, able to work independently, have a collegial attitude, have a solid background in
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hold or will complete in the nearest future a doctoral degree in the above-mentioned fields; are curious, highly motivated and self-driven, able to work independently, have a collegial attitude, have a
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in a dry lab setting and will involve analyzing newly generated and publicly available genomic datasets. We will use both in-house and published bioinformatic tools, including phylogenetics and methods
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computational microbiome research. The specific focus of the project will be tailored to the candidate’s interests and will align with the objectives of the aforementioned consortia. These projects work at the
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world-class facilities, including the 100-m Effelsberg radio telescope , also as a part of the European VLBI Network (EVN ) and the Global Millimetre VLBI Array (GMVA ); the LOFAR DE1 station, part of
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approaches for the analysis of omics, digital, and molecular pathology data, to support precision medicine. We work with real-world data in a highly interdisciplinary environment fostering translational