11 parallel-processing-bioinformatics PhD positions at Tallinn University of Technology in Estonia
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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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                model, which maps online observable process parameters (e.g. spinneret voltage, flow rate etc.) to nanofiber product quality (e.g. morphology, diameter variance, all of which are only observable offline 
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                Description The aim of this research is to enhance the durability and fire resistance of veneer-based wood products by developing and optimizing a sustainable wood densification process. The study seeks 
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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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                on the fabrication of functional materials with enhanced properties for industrial applications using the laser powder-bed fusion (LPBF) process. Particular attention will be paid to alloy design, parameter 
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                Assistant Professor Pablo Daniel En- rique (University of Waterloo) Project goals The main goal of this doctoral research is to develop and apply thermomechanical simulations to study the LPBF processing 
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                landfills instead of reentering the urban value chain. At the same time, existing planning and procurement processes lack unified digital platforms, clear end-of-waste criteria, and incentives for secondary 
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                and in-field operation. The project will investigate co-simulation and multi-domain integration methods, linking ECU DTs with vehicle dynamics, powertrain, and in-vehicle communication networks 
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                process). These empirical, computational and experimental methods and their reliability are often questioned due to various disturbances (wind, wave, current, biofouling, human factor) which can increase 
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                partners. Applicants should fulfil the following requirements: A master’s degree in engineering or science, with a focus on computer/data systems, energy technology, software/hardware, information technology