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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
safety of industrial processes. The Department of Thermal Energy and Process Technology is looking for a PhD Student (f/m/d) Dynamic Process Modelling and Value Chain Assessments for Sustainable Methanol
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to vpajob at tu-dresden.de or to: TU Dresden, Chair of Traffic Process Automation
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In a joint recruitment between the Martin-Luther University Halle-Wittenberg (MLU) in the Faculty of Natural Sciences II - Chemistry, Physics and Mathematics - and the Leibniz Institute of Plant
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located: https://www.fz-juelich.de/en/pgi/pgi-7/research-groups-1/ag-gunkel-1 Your Profile: Completed qualification to enroll for the Master thesis in Physics, Chemistry, or Materials Sciences, with a good
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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-ceramic joining materials, with a focus on interactions during the joining process and under operating conditions Optimisation of experiments, measurement methods and measurement technology, including
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: University degree in mechanical engineering, process engineering, chemistry, physics, or computer science Ability to quickly familiarize yourself with the various issues involved in energy storage and
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particles, depending on its polarity, aromaticity, and concentration Localization of the aromatic molecule within the initial lipid membrane as well as in the target membrane after the fusion process
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optimization of technical processes and products. We present the exciting range of applications of our collaborative software development MESHFREE: https://www.meshfree.eu/ Currently, our team is working
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time