16 phd-nondestructive-evaluation Postdoctoral positions at Chalmers University of Technology
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PhD students in the Automation group, with the primary goal of qualifying for a future academic career. Contribute to research projects within discrete-event systems, supervisory control theory, and
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group. Main responsibilities Conduct research in collaboration with senior researchers and PhD students in the Automation group, with the primary goal of qualifying for a future academic career
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facilities that are highly aligned with the goals of the project. Who we are looking for We seek candidates with the following qualifications: To qualify for the position of postdoc, you must have a PhD degree
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your own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another
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Group within the Quantum Technology Laboratory (QTL) at the Microtechnology and Nanoscience (MC2) department, working in a large team of PhDs, postdocs and researchers. About the research We are seeking
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undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important aspect involves collaboration within academia and with society at large. The position
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analysed using advanced optical techniques such as: High-speed imaging Laser-induced fluorescence Particle image velocimetry Experimental and numerical results will be evaluated and compared to refine both
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of protective materials Perform validation studies to ensure computational model accuracy against experimental benchmarks Collaborate on the development of testing methodologies for protective device evaluation
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own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important
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model accuracy against experimental benchmarks Collaborate on the development of testing methodologies for protective device evaluation Machine Learning Integration Develop and implement machine learning