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devices from motors and actuators to sensors, memories, and emerging paradigms for computation. Despite their technological importance, many fundamental aspects of their behavior remain elusive, especially
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thanks to a complex network of sensors and control systems at various levels, that manage tasks such as air quality control, temperature regulation, and zone-specific environmental conditioning. Advanced
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development of algorithms and large-scale numerical simulations. Your expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and
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the theoretical and algorithmic foundations of AI. A strong commitment to excellence in undergraduate and graduate teaching and mentorship is essential. Preference will be given to candidates who show promise in
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for low-power DC supplies with a very high efficiency and a very wide range of input voltages. Such supply systems are required for applications such as supplying actuators and sensors in facility
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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description ESR15 will primarily focus on the development of metamaterials-based structures and devices that through vibration energy harvesting can exploit structural vibration to power sensors and data
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position (technician, this position) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.
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implementation of the developed models into simulation codes and algorithms. Work closely with project partners from other leading research institutions. Present research findings at international conferences and
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sciences, who ad- dress key issues in AI such as reproducibility, safety, trustworthiness and robustness, and who engage with the theoretical and algorithmic foundations of AI. A strong commitment to