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should be implemented in a model for the trickle bed reactor including relevant mass transfer steps, and parameters in the kinetic model be estimated. Testing of the kinetic model against data
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track its health, recurrent neural networks, particle and/or extended Kalman filters, and inverse parameter estimation methods might be worth exploring. By uncovering the dependency between the cell
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Department. Duties of the position Develop an appropriate experimental setup and utilize suitable methods to characterize the streamer discharge in different insulating liquids. Perform parameter study to
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(m/f/d) in the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is
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. The main focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing