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Optical material acquisition tries to record and reproduce physically realistic effects of different materials, especially their view and light dependence. The challenge is to meet the best tradeoff
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). Originally designed to make video games look realistic, GPUs have evolved into powerful engines for scientific computing. Unlike traditional computer processors, which handle one task at a time, GPUs can carry
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detection, avoidance and path planning methods for mobile systems in any field Expertise on object feature detection, classification and localization Real experience on working with different perception
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, OPS-GA has also developed and maintains many auxiliar tools useful in certain phases of mission operations. Tools and applications are developed based on mission needs, and on different versions
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datasets with varied structures, requiring different analysis approaches. We are looking for a person who is motivated to develop efficient analysis solutions for the P61A data in Python. You can build on
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, scientific computing, etc). Strong scientific computing background, with experience of different architectures (e.g. CPUs/GPUs) and their use in high-performance computing through shared or distributed
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or similar deep learning frameworks GPU know-how: Familiar with GPU workflows and distributed training setups Data competence: Experience in preprocessing, augmentation, and dataset organization; confident
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are one of the largest, most international and most innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day
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visualized and analysed instantaneously during a beam time. Additionally, the varied possibilities at the beamline generate datasets with varied structures, requiring different analysis approaches. We
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in a related field of study (e.g. applied mathematics, computational engineering, scientific computing, etc). Strong scientific computing background, with experience of different architectures (e.g