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data processing descriptions or mathematical formulas. In contrast, combining LLMs with computer vision provides a more flexible framework for understanding and reproducing the computational pipelines
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the running infrastructures. Using cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will
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resulting model will support applications such as cognitive state estimation, brain–computer interfaces, and mental wellbeing monitoring. The learned representations will also enable integration with language
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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. Government defensive missions. Our team provides technical guidance in capability and capacity development for Security Operations Centers (SOCs), National Cyber Centers, and Computer Security Incident
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Master's degree in Electronic Engineering, Electrical Engineering, Telecommunications Engineering, Computer Engineering, Embedded Systems, Mechatronics, Physics, or a closely related discipline. The ideal
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cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will advance our understanding
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of high-performance computer systems You preferably have experience with hydrology, and affinity or experience with agent-based modelling and large-scale data processing with societal relevance You are able
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chemistry Basic knowledge of molecular and cell biology techniques Prior experience with fluorescence, confocal, or electron microscopy and morphometric techniques is welcome Good computer skills and/or
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of underlying 3D scene representations. This requires the designing and developing of specialized computer-generated hologram (CGH) algorithms, modeling the propagation of incoherent light through space