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analyses of public and confidential datasets relevant to the funded projects. Responsibilities include applying causal inference, spatial econometric, and multilevel modeling techniques to examine the
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ACCE+ DLA Programme: Assessing the Future Effectiveness of Spatial Conservation Networks in tetrapods School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof Gavin
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resolution (such as MEG or intracranial EEG) may also be considered, in combination with behavioral recordings and computational modeling. Where to apply Website https://www.unitn.it/ Requirements Additional
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preprocessing; Integration of geospatial and soil data into databases. Data processing and analysis: Application of geoprocessing and spatial analysis techniques; Development and calibration of predictive models
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and transcriptomics. Analyzes spatial transcriptomic datasets to uncover tissue organization and disease states. Develops integrative models combining genomics with pathology images or time-series data
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interpolation methods applied in the environmental sciences: A review. Environmental Modelling & Software, 53, 173-189. [2] Belbeze, S., 2020. http://infoterre.brgm.fr/rapports//RP-70282-FR.pdf [3] Meusburger, K
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changes to hydrometeorological forcing. Geomorphology, 414, 108383, https://doi.org/10.1016/j.geomorph.2022.108383 Eelsalu, M., Viigand, K., Soomere, T., Parnell, K., 2024a. Systematic analysis
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, marking a bold step toward a more collaborative, challenge-driven model of research. Team Science Scientific breakthroughs rarely come from isolation—they emerge when brilliant minds connect. Our Team
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will involve (but not be limited to) applying sophisticated mouse genetic models of cancer and conditional gene targeting, single-cell RNA-seq, spectral flow cytometry, multiplex imaging and spatial
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/Machine Learning engineers. Want to leverage your skills to usher in the era of personalized disease modeling? The Digital Twin Innovation Hub is currently seeking skilled and experienced individuals