37 multiscale-multi-scale-composite Postdoctoral positions at Technical University of Denmark
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competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all
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focus on charge injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling
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power plants and plan large-scale power and energy systems. You are expected to collaborate with multiple industrial partners over multiple projects. We are looking for a self-motivated and team-oriented
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mechanisms. Your experimental work will be centered at the laboratory scale (from microliters to 5 L) using DTU Fermentation Core (https://www.bioengineering.dtu.dk/research/infrastructure-core-facilities/dtu
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-band. We are looking for two postdoctoral researchers, who have excelled in the PhD projects and/or previous postdocs positions to join our team working towards demonstrating chip-scale quantum light
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robust models – and for clinicians, whose goal is to determine when to trust the models. We therefore seek candidates who have strong technical background in working with large-scale deep learning models
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of microbial biofertilizer strains, generating large-scale datasets across all stages—from laboratory experiments (thousands of strains) to in-field testing of up to 800 strains. The scale and standardized
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composition and topography analysis Contamination and surface characterization of metallic components before and after remanufacturing Evaluation of corrosion resistance using both standardized and tailored
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. Responsibilities and qualifications Your primary focus will be to develop a comprehensive database and conduct novel research on how university innovation ecosystems influence the performance and scaling of deep
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optimization, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured