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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
-through system. The objectives of this work are: i) to unveil the driving force of the micro-galvanic corrosion onset; ii) propose several approaches to reduce the micro-galvanic corrosion; iii
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material
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part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This position is
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from any nationality and hold, or expect to hold, a Master’s degree in a related subject. You have a proved track record of academic and research excellence and are fluent in written and spoken English
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. Additional qualifications: It is advantageous to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization
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manufactured at Uppsala University) will be the focus of this PhD project. The objectives of this work are to optimize an experimental setup for simultaneous tension/compression testing and localized corrosion
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suggest the strategies for reducing corresponding degradation rates. The best performing alloys will be tested in vitro at Hydrumedical using in house-developed flow-through system. The objectives
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of biodegra
. Understanding cooperative effects of mechanically assisted corrosion of the Mg and Zn alloys (additively manufactured at Uppsala University) will be the focus of this PhD project. The objectives of this work
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analytical skills are desirable as well as some programming experience, while initial exposure to Finite Element Methods & object-oriented C++ programming language would be a plus, but is not required. We also
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and as part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This