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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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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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area from the simulated measurements using mathematical methods and compare the various combinations and placements of the virtual instruments. You will summarise the results in a report/publication
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of novel sample preparation strategies and the establishment of state-of-the-art analysis pipelines Your qualifications: PhD in Biology, Chemistry, Biochemistry, or a related discipline; several years
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manufacturing machines, sintering devices, etc. characterization of synthesized materials using various analytical methods, e.g. transmission and scanning electron microscopy, X-ray diffraction analysis, etc
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stakeholders involved in sustainable soil and farm management. This network is intended to promote the exchange of knowledge and practical methods so that farmers can make well-founded decisions about their
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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policy impact evaluation, systematic reviews, or evidence synthesis is an asset; Knowledge in statistical software (e.g., R, STATA, or Python) is an asset; A sound understanding of econometrics, meta
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encompasses a comprehensive spectrum of preservation, preparation, and restoration methods, thus offering a diverse field of activity and considerable potential for further development at one of the world's
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founded research area of "Digital Technologies" with a focus on computer-aided high-throughput methods and AI-supported model development presentation of scientific results at international conferences and