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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
approach is based on neural techniques known as SBI (Simulation-Based Inference) [Cranmer et al., 2020]. SBI enables the resolution of inverse problems using generative AI methods and Bayesian statistics
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description The Sars-Covid virus genomic RNA encodes a small number of structural proteins, one of which is the N-protein. This N-protein plays a strong role in packaging the genomic RNA; yet, how this
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comparing models with entirely different structures and parameter counts, whether comparing linear regression against mixture models or decision trees. MML is strictly Bayesian, requiring prior distributions
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How is the Sars-Covid genomic RNA packaged? Job description The Sars-Covid virus genomic RNA encodes a small number of structural proteins, one of which is the N-protein. This N-protein plays a
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integrating literature, in-house, and newly generated experimental data Build surrogate and predictive models that connect composition, molecular structure, synthesis and processing conditions, morphology, and
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familiarity with SLT is not required. We're looking for mathematical maturity (PhD or equivalent) with backgrounds like algebraic geometry, Bayesian statistics, statistical physics, information theory
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PK/PD studies, Bayesian model-based dose-finding approaches, adaptive designs and master protocols, including basket and umbrella trials. You will be expected to build productive collaborations across
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, including active learning or Bayesian optimization. Experience with imaging, time-series or high-dimensional data. Exposure to crystallography or structural biology. Experience with multimodal datasets and
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on the theory of deep learning will investigate questions such as the structure and expressivity of emerging neural architectures relevant to space, such as implicit neural fields, continuous normalising
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constituent-specific remodeling laws that describe chronic changes in myocardial structure and function. You will couple tissue-level cardiac mechanics to systemic hemodynamic and neurohumoral inputs within