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Field
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://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large
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) to train shared models without centralising raw data. In practice, however, individual platforms operate under diverse environmental conditions, sensor calibrations, and system configurations
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primarily on the development, validation, and implementation of the Psychological Referral Optimization algorithm (PRO). PRO is a brief digital e-screening tool designed to support early identification, risk
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position As agile development scales to larger, more complex organizations
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://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large
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of artificial intelligence and consumer behavior. • Designing, developing, and evaluating artificial intelligence (AI)-based techniques and algorithms related to consumer behavior and manipulative online
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: Transparency. As part of this doctoral project, you will develop novel knowledge representation techniques, algorithms for human-in-the-loop optimization, and interactive tools that combine graphical and natural
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Engineering Laboratory (HRE Lab), providing the candidate with access to advanced experimental infrastructure and opportunities to contribute to the further development of the laboratory’s research and
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, collaboration and professional development. The Faculty of Medicine is committed to preparing PhD graduates for diverse career paths. Throughout your PhD, you will develop advanced research competencies alongside
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after deployment, leveraging recent advances in physical reservoir computing, contrastive learning, and biological decision-making paradigms. You will: - Develop and apply decentralized learning