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trends and composition analysis, refractive index determination, and morphology for applications such as environmental monitoring, nuclear non-proliferation, and improving predictive modeling tools (e.g
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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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industrial decarbonisation modelling to support the EU-funded FLARE project. The role will lead the technical development and integration of bottom-up, organisation-level decarbonisation models for energy
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(2024) https://www.nature.com/articles/s41591-023-02702-z Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. https://pmc.ncbi.nlm.nih.gov/articles
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
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of research this position is engaged in: The Bowen lab leverages wide-scale neural recordings, predictive modeling, and continuous glucose monitoring with the goal of building foundational integrated (“multi
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apply AI and data-driven modelling to predict system efficiency - balancing air purification with energy consumption. It will also explore how sensor feedback can control treatment systems and communicate
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theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive dynamics, and population genetics. This position is part of the interdisciplinary consortium