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/Qualifications - Automation or applied mathematics background, with a strong interest in physical models and numerical method - Analysis of partial differential equations, variational approach, Bayesian estimation
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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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