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Ability to communicate complex information clearly Fluency in relevant models, techniques or methods and ability to contribute to developing new ones Ability to assess resource requirements and use
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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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assessments (LCA) to quantify the environmental impacts of proposed processes and compare them with conventional alternatives. Develop process models using industry-standard software (e.g., Aspen Plus, HYSYS
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comprising chemists with expertise in organic chemistry, reactor design and innovative process analytics, and engineers with skills in fluid modelling, Life Cycle Assessment and sustainability. You will
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can successfully predict previously-unknown regulators of seed development through functional genetic analysis of conserved, uncharacterised genes in the model seed plant Arabidopsis thaliana
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. Robert Mann (University of Waterloo), as well as a team of HDR students. The research will explore quantum aspects of physical black holes, collapse models, and the properties of ultra-compact objects
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key properties of quantum machine learning models—expressivity, generalization, and adversarial robustness, and the inter-play between them. These foundational insights will guide the design of novel
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complex, multi-model ecological forecasting workflow. The fellow will gain valuable experience in advanced model development, calibration, and synthesis of the forest succession, fire severity, and climate
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interdisciplinary team comprising chemists with expertise in organic chemistry, reactor design and innovative process analytics, and engineers with skills in fluid modelling, Life Cycle Assessment and sustainability
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capability Ability to communicate complex information clearly Fluency in relevant models, techniques or methods and ability to contribute to developing new ones Ability to assess resource requirements and use