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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modelling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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experiments in gelatine (https://doi.org/10.5194/egusphere-egu25-9211). This model will be tested with analogue experiment results from the MAGMA Lab, run by other members of the project team. The second
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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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, funded by FAR 2024 UNIMORE linea FOMO, and aims to develop authenticity models through environmentally friendly analytical techniques combined with data processing and machine learning algorithms
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EU programme Reference Number OZK-2025-142 Is the Job related to staff position within a Research Infrastructure? No Offer Description Develop and validate frequency-dependent cable and system models
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=26956 Mathematical Modeller (PhD/Postdoc) – DFG Emmy Noether Project “OpTBtreat” (m/f/d
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is looking for a full-time (100%) postdoctoral scholarship holder in the field of statistical shape modelling. Position The project aims to advance personalized musculoskeletal care by transforming
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have: Ph.D. in Biostatistics, Statistics, Bioinformatics, Data Science, or related field; with (i). technical skills such as Proficiency in R, Python, or SAS for statistical analysis and modelling; (ii
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/InstituteVIBCountryBelgiumCityLeuvenPostal Code3000StreetHerestraat 49Geofield Contact City Leuven Website https://jobs.vib.be/j/130090/postdoc-position-deep-learning-for-glioblastoma-sequence-to-function-models Street Herestraat 49 Postal