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) Experience in deep learning algorithms is a plus Ability to work in a highly international team and interdisciplinary project applicants are expected to have excellent language skills in English Opportunity
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February 2026. Typical tasks include: Designing and manufacturing of 3D printed parts Supporting hardware modifications of automated experimental setups Integrating new sensors Running small experimental
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conceptually new type of image sensor based on perovskite materials. Related publications: 1. Tsarev, S., et al., Vertically stacked monolithic perovskite colour photodetectors. Nature, 2025. 642(8068): p. 592
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metal industries. Project background Modern buildings operate thanks to a complex network of sensors and control systems at various levels, that manage tasks such as air quality control, temperature
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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