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. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
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and learning (e.g. student-centred active learning, large classes, small groups, team-based learning, blended and online learning, flipped classrooms, transnational education etc.), and educational
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modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in or experience in environmental exposure
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analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division, Computing and Computational
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, Jose Landivar-Scott, Nick Duffield, Kevin Nowka, Jinha Jung, Anjin Chang, Kiju Lee, Lei Zhao, Mahendra Bhandari, Unmanned aerial system and machine learning driven Digital-Twin framework for in-season
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and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
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management Machine learning, artificial intelligence, and big data analytics in finance Technological innovations for financial services Regulatory issues and challenges in FinTech Digital economy and
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use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for microscopy image analysis are especially relevant. Include a link
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LanguagesENGLISHLevelExcellent Research FieldMedical sciences » MedicineYears of Research ExperienceNone Additional Information Benefits We offer a 4-year PhD position with market conform wages in a large, multidisciplinary
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. ESSENTIAL REQUIREMENTS A PhD inMachine Learning, Computer Vision, Computer Science, Physics, Engineering, Mathematics or related areas. Documented expertise in: Machine/Deep Learning, and possibly Computer