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Field
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bioreactor performance. Developing and applying modeling tools to evaluate enzyme activity, and process performance across scales. Advance bioprocess optimization of complex microbial systems, including multi
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Engineering at NTNU, where computational mechanics, advanced finite element modelling, and artificial intelligence meet. As a PhD candidate, you will work at the forefront of nonlinear simulation, contributing
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model and microsimulation model) Experience in programming language such as Excel, Stata or R or similar Fluent oral and written communication skills in English Intellectual curiosity, analytical rigour
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candidates within Modelling Strength and Failure in Recycled AluminiumAlloys funded through the Centre for Research-based Innovation SFI FAST – Future Aluminium Structures. The positions are linked
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to understand variability in drug toxicity, drug metabolism and drug transport. Examples of this include cell-based models such as induced-pluripotent stem cells, primary human hepatocytes and clinical studies
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using CT scanning, sorption measurements and characterization of the moisture state, modelling of freezable water, frost exposure testing, and mechanical characterization including strength, DIC, dynamic
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teams to explore the long-term effects of repetitive traumatic brain injury (rTBI) in both humans and mouse models. Join us! This PhD position offers you the opportunity to work at the crossroads
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, the weaknesses that have been evoked in the conclusion of most work is the unverified or lack of adaptability of models developed in specific case studies to new environment. Objectives: The PhD research will
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to solve considerably larger problems than before, involving many scenarios for the future. We will use deep generative models as part of the solution process to generate scenarios and guide the search. We
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using CT scanning, sorption measurements and characterization of the moisture state, modelling of freezable water, frost exposure testing, and mechanical characterization including strength, DIC, dynamic