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Field
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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. Experience with Bayesian methods, graph/network analytics, reinforcement learning, or other advanced AI approaches relevant to industrial systems. Experience with geospatial analysis, spatial data integration
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. mixed effects regression models and/or Bayesian statistics; e.g., brms / lme4 packages). Excellent written and spoken English. Desirables (traits that would give you an advantage) Training in evolutionary
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French National Research Institute for Agriculture, Food and Environment (INRAE) | Toulouse, Midi Pyrenees | France | 23 days ago
conferences. Supervision Dr Arthur Kocher (IHAP; MPI-EVA) is the PI of the EpidemioCene project . He studies human and animal disease ecology and evolution using molecular approaches combined with Bayesian
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or more of the following: ecological modelling, dynamical systems, network analysis, Bayesian statistics or probabilistic modelling, mathematical biology, multivariate data analysis. Interest in connecting
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | 6 days ago
analysis, gravity models, Bayesian models, etc.). In this regard, proficiency in software is required: programming languages such as R or Python, machine learning, econometric softwares, data management
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knowledge and/or practical experience in topics such as agent-based modelling, bayesian statistics, causal inference, data visualisation and graphical interfaces, geospatial data analysis, high-performance
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learning or deep learning, preferably with transformer architectures Experience in probabilistic modelling or Bayesian statistics Programming skills in Python, preferably with PyTorch or similar frameworks
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; demonstrated skills in leading a high performing team with a customer services-oriented mindset approach; experience applying AI and/or Bayesian methods within a research context; and proven track record
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observational data, and the application of advanced methods for longitudinal and prediction modelling. You will also conduct methodological research on Bayesian methods and other innovative methodology