71 applied-harmonic-analysis Postdoctoral positions at Technical University of Denmark in Denmark
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). Following the fate of your nanoparticles when applied onto the leaves (TEM, Cryo-SEM, AFM, chemical analysis, spectroscopy, etc). Studying and modelling the interactions of the applied nanoparticles
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meteorological events and how these may impact wind energy based power and energy systems. As well being involved in research projects you will take part in highly relevant scientific advice projects, applying
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: PhD in Veterinary Epidemiology or a related field, or demonstrated experience with epidemiology Strong quantitative data analysis skills Applied understanding of epidemiological principles Demonstrated
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position to develop and apply emulators for Earth System Models (ESMs), with a particular focus on the role of the biological carbon pump in oceanic carbon cycling and climate feedbacks. The research will
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or similar. Background in applied physics/materials science. Experience in STM Experience in programming or writing analysis software is advantageous. Previous experience in nano/micrometer-size device
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, rapidly growing field, we encourage you to apply! Responsibilities and qualifications The primary purpose of this position is to advance cyber-deception research, developing novel deception techniques
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broad interest in information processing in humans and computers, and a particular focus on the signals they exchange, and the opportunities these signals offer for modelling and engineering of cognitive
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Job Description A 2-year Postdoc in Secure Task Offloading for Software Defined Vehicles (SDV) is available in the Embedded Systems Engineering (ESE) section at DTU Compute. The position is part of
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antibiotic resistance in Arctic waters, with a primary focus on Finland, Sweden, Iceland, and Greenland. While the analysis of emerging contaminants will be done at an external certified lab, your working
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simulate wind and solar forecast uncertainties on pan-European level, leveraging latest machine learning weather forecast models Apply machine learning methods to forecast day-ahead and balancing market