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sensing and responding to the chemical landscape surrounding them as well as the chemical signals inside of them. This project is devoted to gather large data sets to investigate links in olfactory receptor
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in glaciology, Geodesy, Earth sciences, remote sensing, or a related field. Strong skills in data analysis, programming, and handling large geospatial datasets are essential. Experience with satellite
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(lubricants, gear oils etc.) from machinery like wind turbines. When we want to remove oil droplets, we need them to merge (coalesce) as big drops are easy to remove. Surfactants can either promote or hinder
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outputs in lidar technology and real-time wind-field reconstruction. Expert in wind turbine response analysis. HAWC2 user expert. Demonstrated expertise in data analysis and signal processing with large
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-friendly materials and a strategy of design for recycling. The Division of Materials and Components has been and is involved in a number of large projects, such as Decomblades, WiseWind, Susschy-Next where
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meetings Potentially participate in Arctic field campaigns Be working with large data sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit
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changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes
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primary tasks will be to: Structure and curate large-scale datasets using open repositories, Design and implement the analysis including code development, Lead the writing of scientific articles and present
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this project, we will develop neural diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also