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Field
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) / InP contact layer (200 nm) / Si substrate The objective of the project is to develop a plasma etching process for this multilayer stack, enabling selective etch stopping on the InP contact layer, which
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in the framework of the BBEST PEPR. The project aims to valorise syngas derived from biomass via the OX-ZEO process. This relay catalytic process combines a hydrogenating metal oxide to produce
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-based fiber panels are generally produced using a dry process and require the addition of heat- fusible synthetic polymer fibers to ensure mechanical strength during handling and dimensional stability in
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mixtures, including information retrieval, random access, approximate search, querying and filtering, encryption, compression, and many other information-processing tasks. Our team is looking for a talented
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the hierarchical architecture of plant secondary cell walls ; Design and optimise sustainable manufacturing processes for the production of nanostructured materials ; Establish relationships between structure
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Tremblay en France, le de France | France | about 2 months ago
partners (www.malar-project.eu ). Your tasks # Providing support during user operation at the XES station (dedicated to high-energy-resolution X-ray Spectroscopy) and coordination with the assigned local
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A postdoctoral position is available to study dynamic processes in early development of insects and mammals. Successful candidates will join a collaborative and interdisciplinary venture in
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: Understanding of the principles of atmospheric modeling, particularly using WRF-Chem. Knowledge of the physical and chemical processes simulated in the model, including cloud microphysics and interactions with
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Requirements Proficiency in intermediate statistical analysis methods (e.g., regressions) and, if possible, advanced methods(e.g., hierarchical models, GLM, etc.). Proficiency in at least one statistical