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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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for analyzing complex ecosystem and environmental datasets. Deep understanding of marine ecosystem processes, particularly within coastal regions. Understanding of underwater light field and its modulating
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
the Max Planck Institute for Demographic Research, Germany, and the University of Helsinki, Finland. To achieve the Center’s vision of unearthing the pivotal social processes that generate health
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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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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energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
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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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-processing, and machine learning textual analysis of the full text of policy documents. Qualitative content thematic analysis is envisioned to compliment structural topic modelling to identify strategies and