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optimization or related inverse design techniques. While this position does not involve developing AI models, it requires close collaboration with AI researchers to ensure data is appropriately structured for AI
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in topology optimization or related inverse design techniques. While this position does not involve developing AI models, it requires close collaboration with AI researchers to ensure data is
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be jointly supervised by Professor Jørgen Ellegaard Andersen and Associate Professor Shan Shan at QM. Candidate profile We encourage applications from PhDs in mathematics and related fields who possess
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parameters as well as downstream requirements. Maintain detailed records of experimental data, process conditions, and system modifications to support scale-up and system integration. Publish scientific
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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this postdoc position, along with an additional postdoc and one PhD position, we will tackle this grand challenge by fabricating and studying electrocatalysts with three-dimensional active site structures. With
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research group as well as the Centre for Cold Studies. These affiliations ensure strong local research support and mentoring. Eligibility and requirements: PhD in History, Rhetoric, Digital Humanities
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PhD in clinical epidemiology Has demonstrated expertise in working with registry data or other types of electronic healthcare databases. Previous high-quality publications Experience with project
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; Collaborating closely with the ENGREENIT’s PhD candidate (starting 12 months later than the PostDoc researcher), supervised by the Assoc. Prof. Emil Draževic, and will jointly develop the heterogeneous
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hold academic qualifications at the PhD level in clinical or clinical epidemiological research. Prior experience in clinical musculoskeletal assessment, inflammatory diseases, the use of registry data