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Field
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submit the following as a single PDF through the University of Michigan job portal: 1. Cover letter describing qualifications, research interests, and fit 2. A CV 3. A research statement (up to 3
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structure prediction. Working at the intersection of generative AI and biophysics, the Fellow will focus on expanding the current framework to model dynamic protein ensembles. As an Empire AI-funded fellow
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of generative AI and biophysics, the Fellow will focus on expanding the current framework to model dynamic protein ensembles. As an Empire AI-funded fellow, you will have access to the Empire AI Alpha and Beta
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statistical modelling, to contribute to an ARC-funded Discovery Project investigating the psychology of how people manage competing demands inside and outside of work. The project develops and tests a novel
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-of-the-art structural modelling and computational protein design approaches to understand and engineer enzymes that modify IgG Fc N-linked glycans. The successful candidate will use tools such as AlphaFold
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data, inspection results and carbon footprint information. Develop, train and validate AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks
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do things, especially considering recent advancements in AI technology. The position will include developing radiomics and deep learning models from contrast-enhanced computed tomography images
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evaluation of the project’s core technical components in expert-in-the-loop agentic AI for manufacturing. Develop process-centric AI methods and software tools for BPMN modelling, Petri/CPN formalisation
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Overview of the Role Are you an ambitious researcher looking for your next challenge? Do you have an established background in hydrology and climate modelling? Are you looking to make a real-world
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of nonstationary spatiotemporal data arising from weather and climate observations/models. About the role Level A - $113K - $121K plus 17% Superannuation and annual leave loading Fixed term – 2 years Full-time (35