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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
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years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems
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NLP is highly welcome. For computational candidates: experience in large-scale ML training (multi-node setups, distributed training) is a strong advantage. Good computational engineering practices
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The power system is changing, largely driven by the energy transition and climate change. The large shares of renewables, both centralized and distributed, are posing new challenges to system
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, particularly with respect to fouling and moisture distribution. Understanding these parameters is essential for predicting long-term track performance and planning maintenance interventions. Project background
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CS Practical knowledge of RL and IL (e.g., behavioral cloning, inverse RL, dealing with distribution shifts) with applications in (industrial) robotics Hands-on experience with robotics or other
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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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during field measurements, capture high-resolution imagery of cloud droplets and ice crystals to determine their size distributions and types. The resulting large datasets (often several terabytes
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workflow Developing seismic monitoring strategies for CO₂ injection, including the design and analysis of surface-based and borehole distributed acoustic sensing (DAS) measurements in preparation