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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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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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problems. Ability to exercise sound judgment in making critical decisions. Bilingual (English/Spanish) – very strongly preferred Have received formal training in implementation science (e.g., graduate level
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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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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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Researcher (R1) Positions PhD Positions Application Deadline 29 Apr 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Permanent Job Status Full-time Hours Per Week 35 Is the job funded through
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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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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database