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to the seven-year eligibility limit may be made for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research and show strong potential
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parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program. We also expect you to have
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, the following are required: – Documented several years of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks – Documented several
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established in the areas of electronic and electromagnetic simulation and design, machine learning and artificial intelligence in electrical engineering, electrical low-frequency and high-frequency measurement
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urban, forest, and market data; developing AI-based forecasting and scenario-simulation pipelines that combine machine learning and simulation methods; and creating visual analytics and human-in-the-loop
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program. We also expect you to have
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following areas: AI and machine learning, natural language processing, large language models (LLM), experience in designing prompts, fine-tuning LLMs, or distributed systems. Good knowledge in one or more of
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
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slowdown at the glass transition, remains a major computational challenge. This Doctoral student project addresses this by combining generative AI models and machine-learned interatomic potentials