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Field
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languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects Knowledge of machine learning and deep learning frameworks, including
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Internet of Things (IIoT) Sensor Fusion and Localization Embedded Systems and Edge Computing Computer Vision and Intelligent Navigation Experience in one or more of the following would be advantageous but is
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This is NTNU NTNU is a broad
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance
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imaging (crucial) Experience with image segmentation, deep learning, or computer vision. Experience with 3D image processing or inverse problems. Experience with experimental research and data acquisition
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designs, techniques and their implementations which are of material significance in addressing important problems). Excellent computer skills and excellent communication skills to effectively interact with
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Strong Python skills and experience with data manipulation Basic machine learning knowledge (equivalent to at least an introductory course) Additional skills (nice-to-haves) Experience with website
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and qualifications Your principal focus will be on applied research advancing bioinformatic analysis, machine learning and computational genomics of microbial pathogens, primarily on bacterial AMR and
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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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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