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Materials Science and engineering or chemistry or related subjects such as corrosion science and engineering. Masters in electronics engineering with prior experience on humidity/corrosion reliability
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between process/system performance, reliability, energy and resource efficiency. This position offers unique opportunities with respect to high level research, training and innovation within manufacturing
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Job Description Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges? Responsibilities and
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performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators (e.g., Kalman Filter
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of the nonlinear structural performance utilizing reliable and computationally efficient numerical structural models. To support the condition (state) assessment, you will also explore the use of advanced estimators
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sensing information from key locations on the offshore infrastructure. In this regard, the research will focus on the assessment of the nonlinear structural performance utilizing reliable and
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life