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systems and control theory. Knowledge of fluid dynamics and related physical modeling. Strong programming skills (e.g. Python, MATLAB, or similar) for data analysis and model development. Ability to work
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). Background in modeling of dynamical systems and control theory. Knowledge of fluid dynamics and related physical modeling. Strong programming skills (e.g. Python, MATLAB, or similar) for data analysis and
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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). Ubiquitous and essential enzymes, ARS catalyse a critical step in protein biosynthesis by charging tRNA with their cognate amino acid. Jordanova Lab reported that dominant mutations in the tyrosyl-tRNA
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“Reinventing Multiterminal Coding for Intelligent Machines (IONIAN).” Why cooperative perception? State-of-the-art autonomous vehicles can miss a critical obstacle when their camera is blinded by sun glare
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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1-D and 2-D modelling approaches fail to capture the complex three-dimensional effects critical to high-frequency, high-efficiency operation in modern converters. The PhD candidate will: 1
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of CMT are aminoacyl-tRNA synthetases (ARS). Ubiquitous and essential enzymes, ARS catalyse a critical step in protein biosynthesis by charging tRNA with their cognate amino acid. Jordanova Lab reported
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highly complex task, as sparse instrumentation does not guarantee direct sensing at all fatigue-critical locations of the substructure’s primary steel. Analytical solutions – so-called virtual sensing
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analysis methods, particularly life cycle assessment and/or ecosystem services assessment, and have a critical and analytical mindset. You are comfortable working with complex datasets, scenario modelling