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reliability of R-Mode, particularly under varying environmental conditions. Key objectives include understanding the physical processes that affect R-Mode signal propagation, quantifying the variability
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, Environmental Sciences, Computer Sciences Proven experience in financial economics, financial risk assessment as well and in climate and ESG ris Interest to work at the interface between research and policy, and
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of the relevant processes with the highest possible resolution. Your Profile A strong background and interest in plant cell biology, biochemistry, physiology and molecular biology We offer Research in a highly
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Association. ZPID is undergoing a strategic extension process aimed at becoming a one-stop, full-service provider supporting the entire spectrum of needs expressed by researchers and psychology professionals
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on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have
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to boron-efficiency and to developmental root growth processes. A unique set of highly boron-efficient Arabidopsis and Brassica napus accessions is ready to be exploited. You will benefit from advanced
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understanding of the processes determing grasslands productivity, nutrient cycling and those leading to grassland soil degradation. • Experience in conducting experiments (field and laboratory). Experience
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information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm
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grasslands. What we expect from you • University degree (M.Sc.) and Ph.D. in Agricultural Science, Biology, Ecology, Environmental Science or a related field. • Thorough understanding of the processes
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Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data