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is using state of the art machine learning tools to extract interpretable latent dynamics. We seek a highly motivated PhD student to develop a predictive computational model using recurrent neural
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Engineering and Bioeconomy (ATB) is a pioneer and a driver of bioeconomy research. We jointly offer the position of a Research Associate / PhD candidate (m/f/d) "The role of livestock slurry as a source of
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with Powerpoint). We expect: A high level of motivation, the ability to work independently and to take initiative; A methodical and systematic approach in the face of many parallel tasks; Structured and
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, preferably with a PhD very good knowledge and proven experience in the field of climate- and texture-dependent calculation of N-dynamics using process-based models (e.g., DNDC, Daycent, Daisy or CANDY
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experiences as well as a completed PhD in chemistry, geochemistry, environmental sciences, chemical oceanography or an equivalent discipline. Experience in instrumental analysis is necessary for successfully
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research environment Presentation of data at scientific meetings within and outside of the group Participation in writing of scientific manuscripts incl. figure preparation The ideal candidate possesses: PhD
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such as glossaries and bibliographies for the volumes Producing content for the series website Required qualifications and experience: PhD, ideally in history, already awarded, on a relevant topic (National
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visualization Basic knowledge in the fields of engineering and materials science A PhD is an advantage, but not a requirement What we offer Our mission is to keep rethinking and innovating the provision and use
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diverse research environment Very high level of written and spoken German and English We offer: Intensive scientific support, close collaboration with cooperating institutions and enrolment in a local PhD
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the new institute strategic extension TropEcS Publish in the field of data science and technology applied to the marine coastal tropics Supervise group members (Bachelor, MSc and PhD students, postdoctoral