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outcome-prediction models in the DBS literature, the PhD will implement a structured, multi-tiered analytical framework that systematically compares classical regression techniques with modern penalized and
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microstructural descriptors that are physically meaningful and predictive. Probabilistic surrogate modelling and digital twin construction. The extracted microstructural descriptors will be used to learn a
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reports acceptable to the Principal Investigator and funding agencies Other duties as assigned Unit URL https://www.uidaho.edu/natural-resources/research/fish-wildlife-coop Position Qualifications Required
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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for the anticipation of extreme stresses on structures. The second step relies on modeling the accidental cascade. Bayesian Networks provide a formal structure for the causal chain (Flood → Loss of containment → Leak
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belowground; - development of SDM modeling structures that best reflect plant use of multiple resources (e.g., interactive vs. substitutable resources); - testing the application of resource colimitation theory
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“Bayesian Enhanced Tensor Factorization Embedding Structure (BETTER)”, and this PhD project specifically aims at developing a unified, scalable, and interpretable framework for tensor analysis. Specifically
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, XRF, isotopic, and tephra analysis, alongside the construction of Bayesian age–depth models using radiocarbon, 210Pb, and tephrochronology. Candidates with experience in metagenomics (sedimentary aDNA
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., 2020). The upper trophic levels (marine mammals and birds) are accurately represented through a co-construction approach based on consultations with experts. A monospecific approach is adopted for marine
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | 7 days ago
, institutional, and conservation factors such as MPAs have shaped them. Examining how climate risks interact with structural factors to create nutritional vulnerabilities. Identifying strategies for building