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for a closed-loop decision support system that can be verified in rehabilitation in many health conditions. This position is open for a postdoctoral researcher in the field of transparent machine learning
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position in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers
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machine learning to develop an automated design process of mechanical walking aids, analyse gait patterns and make biomechanical simulations embedded in the generative mechanism design process. In
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variability described in the data by means of uncertainty aware calibration and Bayesian estimation Include how experts currently operate and acquire feelings for the machine they are driving, also based on a
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construction or related fields Knowledge and experience in data analysis and database management, as well as emerging technologies applied to the construction sector, such as BIM, scanning, machine learning
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characterisation of diagnostic and therapeutic tracers Tumour imaging, clinical oncology and data analysis Semiconductor detectors, nuclear physics and Monte Carlo simulation Machine learning, deep learning and
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(or shortly thereafter). Project background The goal of this project is to leverage advanced machine learning to develop an automated design process of mechanical walking aids, analyse gait patterns and
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, machine learning, modeling, and custom hardware, we test our solutions in various real-world projects with industry. Project background We foster a culture of continuous improvement, transparency, and no BS
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, programming and statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results
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microfluidics and/or analytical chemistry in an asset Computer skills: Word, Excel, Powerpoint, some experience with at least one programming language language: fluent English self-motivation, scientific