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. Specifically, NIR sensors, hyperspectral imaging coupled with standard or macro lens, spatially resolved spectrometry, evolving plots, and FTIR will be used for the non-invasive characterisation of raw material
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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). Methods include sensor-based technologies, external and internal exposome approaches, and co-creation and participatory research methods. This PhD position seeks to contribute to and build upon work being
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in the adaptation and improvement of the algorithms required for the aggregation and provision of flexibility to the grid, the optimized management of an energy community, and the intelligent operation
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of an image analysis algorithm for particle tracking and speed quantification. Requirements for candidates: Essential: BSc and MSc in biochemistry, biology, biophysics, biotechnology, biomedical engineering
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-driven proteomic. Who are we looking for? A motivated researcher with strong programming skills and knowledge of machine learning algorithms, bioinformatics, proteomics, and molecular biology, keen to
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, including data obtained from camera trapping and large databases containing data on the movement of species tracked by GPS. · Statistical analysis of data in R, which includes programming of algorithms