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, cloud platforms, Docker). · Experience with GIS/spatial analysis and traffic simulation or microsimulation tools. · Evidence of scholarly productivity (peer-reviewed manuscripts) and
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, benchmarking, and validation methods • Microservice-based, cloud-native, edge, and distributed software systems • Interoperability frameworks, data integration, and cross-system communication • Digital twin
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— from Cloud to Edge. Our research aims to enable scalable, low-latency, and resource-aware deployment of large foundation models. Expected start date and duration of employment This is a full-time
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with: Experience with web-GIS development or geospatial data visualization. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API
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model predictive control, machine learning, or reinforcement learning. Experience with IoT, edge computing, and cloud integration. Proven ability to contribute to research funding proposals
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, contrastive learning, or representation learning approaches Experience with high-performance computing, cloud platforms, or distributed training Prior experience working in a collaborative biomedical
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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). We are looking for a person with: A PhD in computer science or a related field, with a software systems profile: distributed systems, cloud or edge computing, simulation, digital twins, model-based
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. Few people today can work across both, so the skills you build here are scarce and in high demand. Our graduates will be ready for roles at cloud and datacentre operators, energy companies, grid
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the Wallenberg AI, Autonomous systems, and Software Program (WASP) whereby you will have the opportunity of collaboration with top researchers within cybersecurity, networking, AI planning, and cloud