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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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will be done using finite element modelling (Comsol) · Development/adaptation of signal conditioning electronics · Integration of the harvester into a real tire · Tests in the tire
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: · Investigation of geometries for an efficient transfer of strain from the tire into the ceramic. The design optimisation will be done using finite element modelling (Comsol) · Development/adaptation
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advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and deep learning. He/she will support the development of an improved forest RTM that can
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and uncertainty mapping at satellite, airborne and drone levels. You will explore advanced retrieval techniques, including spatio-temporal regularization, and hybrid methods with machine learning and
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environment Background in plasma assisted deposition processes, metal and organometallic materials synthesis and characterization, knowledge and/or experience in prototyping Additional competencies: proven
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Background in plasma assisted deposition processes, metal and organometallic materials synthesis and characterization, knowledge and/or experience in prototyping Additional competencies: proven autonomy in
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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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Researcher will work on cutting-edge bioinformatics methods in relation to the gut microbiome. The applicant will provide computational support to ongoing projects and have the opportunity to pursue their own
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include: Intrinsic uncertainty estimation in MLFFs (epistemic & aleatoric uncertainty) Negative log-likelihood and calibration methods for force-field training Feature-space and orbit-based analysis