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SD-26083 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF METAL ORGANIC FRAMEWORKS F...
chemicals and fuels. The postdoctoral researcher will work on the chemical vapor deposition and engineering of metal organic frameworks for energy applications (WP4). Comprehensive characterization methods
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SD-26084 – POSTDOCTORAL RESEARCHER IN THE CHEMICAL VAPOR DEPOSITION OF COVALENT ORGANIC FRAMEWORK...
chemicals and fuels. The postdoctoral researcher will work on the chemical vapor deposition and engineering of covalent organic frameworks for energy applications (WP3). Comprehensive characterization methods
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SD-26085 POSTDOCTORAL RESEARCHER IN THE OXIDATIVE CHEMICAL VAPOR DEPOSITION OF FUNCTIONAL BUILDIN...
chemical vapor deposition of unexplored building blocks for the synthesis of functional thin films (WP2). Comprehensive characterization methods, including surface analysis (XPS, Raman, SIMS, HRMS, TEM, FTIR
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! Education · PhD in computer science, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods
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monitoring and Fault Detection, Isolation, and Recovery (FDIR) for space-borne and robotic systems. The candidate will carry a leading role in this area and support PhD candidates in their thesis research
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role Develop innovative methods and data-driven AI tools for highly dynamic SatCom systems Implement and open-source proof-of-concept
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. Specifically, the project will combine 30 years of Danish health data at the service of hundreds of women with endometriosis, recruited through online platforms. It will use AI-enhanced methods to handle
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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demonstrate excellence in formal demography and demographic methods. The Department of Demography (https://demografie.univie.ac.at/) at the University of Vienna was established in 2019 and comprises a team of
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of the treated fibres using advanced characterization methods (e.g. AFM, XPS, ToF‑SIMS, DVS, tensile testing, X‑ray tomography). Analyse and correlate processing parameters, microstructure and properties, and