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Field
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the investigation and realization of improved microwave probe design, data processing, and visualization techniques to provide a robust method of data analysis, flaw characterization and sizing. AI/machine learning
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and industry. This is an exciting opportunity for a suitable candidate where he or she will be exposed to the latest technology, learn from experts working in the area and prepare for an exciting career
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. Advanced modeling techniques, such as surrogate modeling, machine learning, and physics-informed neural networks, will be applied to accelerate simulations and enable real-time performance. A strong emphasis
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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2 Oct 2025 Job Information Organisation/Company Tallinn University of Technology Research Field Computer science » Programming Computer science » Other Engineering » Materials engineering
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication
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and Computer Vision Excellent programmer in Java / C / Python or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical
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equivalent to a two-year master's degree in mathematics, physics, computer science, electrical engineering or closely related fields with a focus on computer vision, machine learning or robotics A strong
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machine learning with the logical reasoning and semantic understanding of symbolic AI (often referred to as material and design informatics) is being developed for the accelerated discovery and development
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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