37 finite-element-methods-"Multiple" Postdoctoral positions at Technical University of Denmark in Denmark
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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performing educational research (mix-methods, surveys). Your primary tasks will be to: Implement full-stack applications, including an AI model in the back-end and GUI (in HTML); Deploy AI models both locally
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of this postdoc position is to develop and employ multiple in-situ spectroscopic techniques, including, but not limited to, surface-enhanced IR and Raman, to investigate the reaction intermediates
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Job Description We offer an exciting postdoc position dedicated to developing methods for detecting performance disparities in foundation models for fetal ultrasound and understanding what causes
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to the air. This project aims at developing analytical methods and capacity to sample and quantify volatile PFAS compounds and air emissions from Danish landfills and treatment plants. The project is carried
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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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of solid oxide cell and stack materials Commissioning, modifying, and maintaining testing equipment Developing new mechanical testing methods Preparing samples for mechanical testing, and carrying out post
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sustainable technologies, methods and solutions, and to disseminate this knowledge to society and future generations of engineers. The Department has approximately 300 staff from more than 30 nationalities
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without incurring prohibitive computational costs. Unlike standard sequential sampling methods, the project will explore batch-based active learning, prioritizing diversity and informativeness in data
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invites applications for a postdoctoral position within a dynamic research team dedicated to understanding and improving taxation behavior through behavioral and experimental methods. This is a unique