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and policy. Phase 2: Comparative Analysis - Apply multiple analytical perspectives to critically examine the collected materials. Phase 3: Model & Method Development - Map findings onto established
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. The successful candidate will work in an interdisciplinary team investigating the diffusion of radionuclides (U, Pu, Am) and decay products (Zr) through rock minerals triggered by colloids, as well as methods
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algorithms and methods for calibrated Bayesian federated learning for trustworthy collaborative Bayesian learning on data from multiple participants. The project will develop new methods, theory, and
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multiple scales, while Multiobjective optimization strategies ensure improvements in efficiency across various biomanufacturing scales. Expected results: 1) Development of innovative bio-based production
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aimed at developing novel Artificial Intelligence–based methods and software to assist physicians with: Disease classification Treatment decision support What-if analyses. Although the developed methods
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methods to estimate food passage do not measure food directly, are impractical for many species, and often require unnatural conditions to administer. This new method directly measures the transit and
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to apply mathematical modelling methods to study adrenal gland steroid biosynthesis dynamics and their spatial relationship with adrenal tumours found in Primary aldosteronism (PA) and Mild autonomous
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exceeding $2.5 million. Research activities are conducted in multiple research laboratories at the Department and research centers in the College and the University. Job Description: The Department
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pseudorange correction through multiobjective optimisation. The research will explore multiple classes of constraints that will be embedded as objectives: Internal pseudorange consistency: ensuring
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training network and aims to apply mathematical modelling methods to study adrenal gland steroid biosynthesis dynamics and their spatial relationship with adrenal tumours found in Primary aldosteronism (PA