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. Desirable Familiarity with supply chain management, operations, or organizational contexts. Experience with advanced statistical methods (e.g. multilevel modelling, causal inference, Bayesian methods
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work closely with the other PhD candidate of PAST, who creates high-resolution proxy-based reconstructions of the same paleoclimate. Together, you apply a Bayesian statistical framework to contrast and
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varying material properties. The resulting response will be analyzed using techniques such as Monte Carlo simulations. Identifying the variability of the model parameters using Bayesian inference
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programming techniques (e.g., techniques for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference
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the genetic association between different trait definitions for feed intake, efficiency and methane. Evaluating the consequences of selection on different traits for different breeding scenarios and objectives
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ensure the long-term resilience of coastal and urban infrastructure. Your development A personalized training programme will be established, tailored to your training needs and career objectives
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allow us to better understand the large-scale impacts of these changes for global water supply. A personalised training programme will be set up, reflecting your training needs and career objectives
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aligned with the project’s objectives. Conduct a mapping and qualitative case studies of social innovations in academic systems (e.g. in the areas of funding, ethics governance, academic activism) in
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Guardian Oversight Systems. The position is embedded in Work Package 4 (WP4): Secure Data Exchange, led by prof. dr. Willem-Jan van den Heuvel, and is central to the technical and scientific objectives
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an Article 9 certificate to work with laboratory animals is a pre-requisite; a strong (proven) interest in numerical and computational/physical modelling of force transmission onto objects is preferred and/or