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processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from investigating fundamental properties
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Doctoral Researcher in statistical signal processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from
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regions to capture high-resolution spatial–temporal environmental data (sedimentation, meltwater flows, vegetation changes, landslides). Process and analyse geospatial datasets, including 4D point clouds
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(sedimentation, meltwater flows, vegetation changes, landslides). Process and analyse geospatial datasets, including 4D point clouds from UAVs and TLS, integrating them into adaptive design frameworks. Develop
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modeling (e.g., Rhino/Grasshopper, Phyton, Unity, Blender). Point cloud processing (e.g., CloudCompare, Autodesk ReCap) and/or GIS. Immersive simulation environments and interactive design tools. Experience
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes
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with mechanical motion. In our more applied research, we lay the foundation for a new generation of devices that use various types of microwave-optomechanical effects for efficient signal processing. We
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research, we lay the foundation for a new generation of devices that use various types of microwave-optomechanical effects for efficient signal processing. We have realized quantum-limited microwave
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-matter Bose-Einstein condensates (BEC) using optical signals in the telecom and infrared (IR) spectral ranges. Project background: The control methods are enabled by strong exciton-photon and exciton
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Devices (QCD) group at the Department of Applied Physics. In this position you have a chance to make history by demonstrating some of the first experiments of the future quantum-computer technology that is