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of E2E models. By embedding knowledge of traffic rules, environmental factors, and human driver behaviors into generated scenarios, the approach will provide a scalable and explainable method to test the
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process (process-specific design) (2) Optimization of the LPBF process parameters to achieve desired microstructure and material properties, (3) In-depth materials, and property testing and (4) Prototype
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new paradigm in the design, testing, and validation of Electronic Control Units (ECUs) for Connected and Autonomous Vehicles. By developing high-fidelity Digital Twins (DTs) that combine functional
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. Responsibilities and tasks Compile an analytical framework for examining experimental approaches to analyze green fire-retardant pretreat- ment methods before and after wood densification. Study and test the
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on the electrical machine optimization to achieve high energy-efficient drive system. The practical part of the work will be testing the control model with a prototype machine in the research laboratory. Research
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analysis by testing various in-situ applications such Energy Saving Devices. The collected data could be used to build a digital twin. The aim of this PhD project is to demonstrate clean maritime systems
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in simulation, modeling, and process optimization. TalTech is equipped with up-to-date laboratories for powder metallurgy, additive manufacturing, laser processing, and materials testing
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techniques with open-source autonomous driving software (for sim- ulation and testing) Applicants should fulfil the following requirements: a master’s degree in engineering sciences (preferably in computing
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the candidate real-world engineering challenges and access to industrial platforms for testing and implementation. Responsibilities and (foreseen) tasks Synthesis and implementation of power electronic converter
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at least B2 level (IELTS Academic, TOEFL iBT, Cambridge English or Pearson Test of English Academic) or a written confirmation by an official from your degree awarding institution that you have completed