10 machine-learning PhD positions at Eindhoven University of Technology (TU/e) in Netherlands
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-making processes. This situation underscores the pressing need for advanced machine learning techniques that not only deliver high performance but also provide interpretable insights into how conclusions
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Science, Data Science, Artificial Intelligence or a related technical field. Experience and knowledgeable in AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven approaches
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in machine learning (ML)? This PhD position offers a unique opportunity to contribute to cutting-edge research in algorithmic fairness, ensuring that automated decision-making systems produce equitable
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research at the intersection of Interaction Design (IxD), Human-Computer Interaction (HCI), and Artificial Intelligence (AI) If you are passionate about designing the future of Human-AI interaction and
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topic. Knowledgeable in system development, including front-end and back-end development. Familiar with AI techniques (e.g., machine learning, deep learning, predictive analytics) and data-driven
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design and simulation. Familiarity and some knowledge on AI, machine learning and neural networks is preferred. Familiarity with IC design tools and tapeout flow. Proficiency in relevant software tools
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Electrical Engineering, Computer Engineering, or a related field. Strong background in analog and/or mixed-signal circuit design and simulation. Familiarity and some knowledge on AI, machine learning and
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our research team in cryptography. The ideal candidate will have a strong background in mathematics, computer sciences, engineering, or a closely related field. The candidate must be highly motivated
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functioning of the lithographic equipment's, hydrophobic coatings are applied in some parts of the machines, for example to protect surfaces from contact with water, oils or contaminants. These coatings
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interest in cybersecurity. For track 1 experience in network monitoring, collaborative security and/or machine learning (track 1) is welcome, but not required. For track 2, experience with Internet of Things