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Field
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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Position Description The project will focus on the development and application of advanced data-analysis techniques for gravitational-wave science, including machine learning and deep learning
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directly with speaker communities to ensure the technology is genuinely useful to them. You will gain deep expertise in machine learning and natural language processing, access to high-performance computing
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
: Good programming skills, preferably in Python, and strong analytical abilities. A solid background in machine learning, computer security, privacy, distributed systems, or a closely related area
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time
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check the minimum entry requirements for the PhD . Applicants must also satisfy Monash’s English Language Proficiency requirements; Demonstrate knowledge of machine learning, medical image analysis
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system integrates robotics, automated sample handling, sensor networks, imaging systems, cloud computing, and machine-learning-based analytics. The research work at NTNU will focus particularly
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, and machine-learning-based analytics. The research work at NTNU will focus particularly on automation, robotics, mechatronic design, sensor integration, and intelligent experimental systems required
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine