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focus on how interactions between species at different trophic levels shape these responses. The project combines (1) analysis of long-term datasets to quantify historical changes in the distributions
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. The successful candidate will work on field-based experiments, data collection, and analysis, focusing on understanding the interaction between floral resources, pollinator activity, and apple yield outcomes
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technical work packages: WP1 Annoyance from wind turbines WP2 Wind turbine noise data collection and analysis WP3 Wind turbine noise source modeling WP4 Wind turbine noise propagation modeling WP5 Wind farm
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training component comprises 30 ECTS (10 ECTS are granted for compulsory courses, 20 ECTS are granted for elective courses) and the research component (dissertation) comprises 150 ECTS. The compulsory
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announcing a PhD position in Logistics focusing on Immersive media technology environments in the analysis of consumer response in circular value chains. The PhD position is organized under Department
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and some familiarity with the preparation of tissue sections Experience working with tissue sections or organoid samples for bio-imaging applications Familiarity with image analysis tools such as MATLAB
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challenges in machine learning for short multivariate time-series analysis. By developing a multiway and multitask learning framework with built-in explainability, the project aims to deliver clinically
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this emerging field in close cooperation with our research group and the industry. The goals of the PhD project include: Analysis of the sources of CO2 with potential for delivery to the CCS facilities in
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learning is required. Experience with spectral wave modeling is an advantage. Experience with ocean modeling is an advantage. Experience with metocean data analysis is an advantage. Experience with git
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computational skills (using R, modelling software, working on a remote linux-based server) and experience in analyzing Next Generation Sequencing data, including PCA, outlier analysis, GO-term enrichment analysis