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Field
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. The project will be conducted within the Process and Energy Department at the faculty of Mechanical Engineering at TU Delft, under supervision of Dr. Mahinder Ramdin and Prof. Rene Pecnik. Job requirements The
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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of future urban scenarios? The postdoctoral researcher will develop an integrated analytical framework connecting: Verticalisation → 3D urban morphology → environmental processes → climate and flood impacts
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parties. Contribution to any project-level digital humanities tasks like dissemination of OA deliverables via HAL-SHS, creation of short videos, writing and publishing of shopr academic blog posts
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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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and communication across multiple modalities, such as text, pictures, audio, and video? Join the large scale HAICu project to help unlock the potential of cultural digital archives through multimodal
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minority non-European language is in possession of extensive transcribed/translated video-recorded data from conversation in a minority non-European language, gathered in primary fieldwork in home/village
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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. The activity of the IMAGES team of the IDS department in LTCI covers many aspects of the processing, analysis and synthesis of digital images, volumes, and videos. A particularity of the team’s work is
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metallurgy which is the liquid copper infiltration (LCI) in copper-contaminated steels leading to cracking during steel processing. While LCI is a known issue in conventional steel recycling, it becomes