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WaterWeave project, which focuses on innovative solutions for monitoring and the sustainable management of water resources. The fellow will develop machine learning and cloud computing techniques to estimate
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and computer programming skills. The objective of this research is failure and damage detection in the petroleum artificial lift process using the operational data signal analysis (time series analysis
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position within a Research Infrastructure? No Offer Description The project is an international collaboration to synthesise current knowledge about mountain biodiversity and related ecosystem services in
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, Raman spectroscopy, ultraviolet-visible spectroscopy – UV-Vis), as well as optical, electrical, and photoluminescence measurements, including Physical Properties Measurement System (PPMS). Activities also
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: This project is related to machine learning for Urban Informatics. In this context, the intersection between the urban infrastructure and digital technologies plays an essential role. The aim is to develop
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applicants should register via the form: https://docs.google.com/forms/d/e/1FAIpQLSefNuCcUNVmY7xicw2ZPn_n_dyMCNMbVGpBQAcK8yNMTRaiqQ/viewform Information about the position: https://drive.google.com/file/d
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for evaluating platelet function (especially point of care; techniques like electrical bioimpedance and optical aggregometry); assembling and handling databases (Excel and/or RedCap); basic knowledge of statistics
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machine learning (ML) algorithms to identify previously unknown correlations between synthesis parameters (inputs) and optical, electronic and chemical properties (outputs), such as quantum yield, light
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multifunctional characterization. The candidate should correlate high-resolution morphological and electrostatic data (obtained by AFM, KPFM, and SKPM) with electrical and optical measurements in complete devices
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staff position within a Research Infrastructure? No Offer Description The project aims to develop sustainable oil and gas production in FPSOs using clean electric power — initially as a complementary