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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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properties. In parallel, they continuously sense and respond to diverse mechanical cues from their environment, including adhesion, stiffness, tension, shear, pressure, and confinement. These cues
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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering practices for scientific software (version control, testing, continuous
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and outbound prospects related to any outreach and sales activities for SNAI. Devise and implement sales formats enabling multiple prospects to engage with SNAI offerings in parallel (thematic events
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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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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-phonon coupling elements. With these, dedicated scattering rates can be computed and then used in quantum transport simulations. Down the line, we aim to pre-train a common GNN backbone model capable
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organised individual to support multiple experimental and computational research groups. The successful candidate will contribute to both a collaborative research network and institute-wide activities