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Field
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this PhD project, you will build a self-driving laboratory platform that will help solving outstanding questions at the forefront of (photo)chemistry by implementing automated spectroscopy workflows
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: procedural or node-based production, AI or machine learning, or technical art. Applicants should have demonstrable programming or scripting experience and the ability to develop and evaluate working software
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on clinical complications, and use machine learning to develop and validate predictive models to identify high-risk patients. The research aims to individualise inpatient care, reduce hospital-acquired
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DTU Management invites applications for a 3-year PhD Scholarship associated with the project “Brains in Motion: Explaining How Humans Learn and Adapt to Navigate Urban Environments Using Artificial
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning and neural networks Basic
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research