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-dimensional niche models, and applying advanced Bayesian spatio-temporal methods. You will: Build n-dimensional abiotic niches for >6,700 species and estimate population positions within them. Quantify niche
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. Butler, C. Goncu, and L. Holloway. Tactile presentation of network data: Text, matrix or diagram? In CHI2020, pages 1–12, 2020. I. Zukerman et al.˙Exploratory Interaction with a Bayesian Argumentation
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will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies
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the virtual embryo; and Bayesian Inference to calibrate model parameters and identify developmental control points. You will also gain experience in the simulation-experiment loop, where computational
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/or data science (e.g., machine learning and AI, Bayesian methods, predictive analytics). In addition, all faculty members are expected to conduct research in the subdiscipline of their expertise (e.g
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. Fields of knowledge: Techniques for model selection, evaluation, and comparison of methods; Algorithms for regression (e.g., linear, Bayesian, regularization kernels); Algorithms for classification (e.g
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California State University, Northridge | Northridge, California | United States | about 13 hours ago
, Bayesian methods, predictive analytics). In addition, all faculty members are expected to conduct research in the subdiscipline of their expertise (e.g., quantitative, data science, clinical, social
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) Uncertainty quantification, 4) Model interpretability. Experience with other deep learning methods, such as Convolutional or Bayesian Neural Networks, Simulation-Based Inference (SBI), Normalizing Flows
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/or data science (e.g., machine learning and AI, Bayesian methods, predictive analytics). In addition, all faculty members are expected to conduct research in the subdiscipline of their expertise (e.g
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 15 days ago
specifically, we use simulation-based inference (SBI) [1], a Bayesian approach that leverages deep generative models, such as conditional normalizing flows and score-diffusion models, to approximate