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behaviour of the material. FEA Modelling: Employ Finite Element Analysis (FEA) to model defects, offering a structural-level understanding of the impact of defect location, size, and type. Manufacturing
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setups for learning, e.g. first for how to control attitude and ego-motion, with all required elements instilled in a spiking neural network. We strive for developing a self-supervised learning approach
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they collide in mechanical contact (less particles generated), and new design methods that use compliant machine elements to eliminate sliding surfaces. The three PhD-students will be working closely together
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Engineering, Civil Engineering or a comparable discipline. Experience with the Discrete Element Method (DEM). Experience with Machine Learning and Design Optimisation. Demonstrable affinity with industry
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element in this newly devised concept. In particular, we expect a shift in the decision-making process, which is currently in the hands of transport operators and freight forwarders. The PhD candidate is
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paradigms enables drones to dynamically adapt their actions based on environmental feedback and past experiences. The PhD candidate will develop innovative planning algorithms which exploit elements
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how it will change due to climate change and human impact. You will be part of a team of 2 PhD students and 2 Post-docs who will combine ground-based experimental data, satellite data, radiative
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of CoCoGel to develop elements of your project. A secondment of up to 8 months will be hosted by InProcess LSP, a scale-up company that develops process analytical technology for in-line characterization of
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of CoCoGel to develop elements of your project. A secondment of up to 8 months will be hosted by InProcess LSP, a scale-up company that develops process analytical technology for in-line characterization of
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vitae (CV). The names and contact details of two referees (position, professional address, and e-mail). A letter of motivation (max. 1 page). A copy of your master’s degree (including transcripts). It is