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(UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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Scene Understanding Detection and Identification of Objects (SSUDIO) project. The purpose of this project is to develop scene understanding from 3D scans of ships by applying machine learning/computer
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, including selecting program format for final output, capturing/importing media, organizing raw media, editing footage and sound files, creating and inserting static and motion graphics, titling, adding music
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maintaining maker space hardware, software, 3D printers, and other technology including microscopes, iPads, AV equipment, tracking software, calculators, graphic design/video editing software, and other related
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2027 - 10:44 (UTC) Country Luxembourg Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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ultraviolet and a aquatic hyperspectral lidar. The development is done by raytracing, Computer Aided Design and 3D printing. After calibration, the instruments will be tested in field for applications within
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external partners, and received grants from 39 funders. Our expertise include database development, computational ontologies, natural language processing, computational linguistics, data visualisation and 3D
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. formatting, tables, math functions, merge functions, graphics, charts) and various computer skills, including Excel, Microsoft Word, PowerPoint, Microsoft Access, Microsoft Outlook, SharePoint, electronic
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assigned. Qualifications: Bachelor's degree in a STEM field or Architecture required. Two years of previous experience in a Maker Space/Fabrication Lab environment. Experience with 3D Printers (such as Bambu
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of the following courses: Introduction to Toy Design Drafting and Technical Drawing Advanced Hard Toy: Design & Engineering Advanced Computer Graphics in Toy Design Adjunct instructors deliver relevant