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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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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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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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suite of thin-film deposition and processing setups heavily customized for exploratory materials research. This includes the “big three” techniques (sputtering, evaporation, and CVD) with access to 5
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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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, which might just be the right project for you. The project is integrated in a large effort financed by the Novo Nordisk Foundation. It is led by the Department of Plant Biology at the University
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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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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
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well as abroad. Your primary tasks will be to: Using automotive lidars for detection of wind turbine blade deflection Development of efficient ways to analyze the automotive lidar data Develop the technology to