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pay of 8%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An
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own learning process . An excellent technical infrastructure, on-campus children's day care and sports facilities. Unlimited access to the modern on‑campus TU/e Student Sports Center at an
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. Furthermore, you will collaborate closely with local and international colleagues working in both experimental and theoretical fields to enable you to learn and execute world-leading research. Job requirements
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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society. From healthy aging to e-health, and from training top athletes to social media as a teaching tool. We combine three academic disciplines: psychology, movement sciences and education. A
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within the overarching theme of language variation. Specifically, one project will focus on morpho-syntactic structures across West, East, and North Frisian, while the other will focus on dialectology with
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to understand how complex biological functions emerge from interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362789/phd-learning-interactions-in-co
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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute
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researchers from diverse backgrounds. Good communication skills and a willingness to learn are important for working effectively within and beyond the consortium. Candidates should hold a Master’s degree in
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied