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-based control of multilayer electrospinning. The task of the PhD student is constructing a scalable, multiparameter model, which maps online observable process parameters (e.g. spinneret voltage, flow
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focus on developing new power electronics and control architectures to enable the operation of residential HVAC systems (heat pumps and heat recovery ventilation units) in droop-controlled DC microgrids
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quality models for multilayer membranes, and 2) no robust and scalable methods for model-based control of multilayer electrospinning. The task of the PhD student is constructing a scalable, multiparameter
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control tools (TEXTURISE project). The TEXTURISE main objectives are: - To identify the key factors (such as raw materials characteristics and processing conditions) influencing the structure building
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the MyoSuite framework to: Development of computer models of the musculoskeletal system incorporating neural control pathways Train NMS model control policies via RL Your seconday tasks will include: Using
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, powder-controlled Directed Energy Deposition process (DED-LB) for metallic Functionally Graded Materials (FGMs). This advanced additive manufacturing technique allows complete three-dimensional design
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to: Development of computer models of the musculoskeletal system incorporating neural control pathways Train NMS model control policies via RL Your seconday tasks will include: Using learned NMS model control
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that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon models and neural control pathways (e.g., CPG-like and
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GRaded Additive manufacturing through closed-loop Directed Energy Deposition process control (GRADΞD). Functionally Graded Additive Metals (FGAM) present unseen design and manufacturing opportunities
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Are you passionate about dynamical systems and system theory? Are you interested in making the design process of complex dynamical systems simpler by smart new tools for systems engineering? Are you