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. (2017). Beyond prediction: Using big data for policy problems. Science, 355(6324), 483–485. Barocas, S., Hardt, M., & Narayanan, A. (2021). Fairness in Machine Learning. Retrieved from https
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statistics, together contributing to a deeper understanding of the basis of human brain connectivity and brain function. You have affinity with working with large datasets and have knowledge of data analysis
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and arms for both autonomous and prosthetic applications. If you’re excited by all this, we encourage you to apply. The opening: In this project, you will develop: Detailed, large-scale computer models
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). PhD students in our department receive excellent training and ample opportunities for feedback. In addition to standard required course work, students typically take courses in machine learning, (micro
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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the SCM section will fill a maximum of one PhD positions this year that can be on any of these topics. Machine learning for stochastic last-mile deliveries In recent years, stochasticity has received
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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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research (e.g., combining big data or machine learning with in-depth fieldwork) can also be pursued. Method selection and mastery are viewed as part of the PhD learning process, guided by supervisors and
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host a PhD day during which the students present their work and receive feedback from the department at large. Besides, we organize weekly lunchclubs during which both students and faculty can present
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applications. If you’re excited by all this, we encourage you to apply. The opening: In this project, you will develop: Detailed, large-scale computer models of the composite human neuro-musculo-skeletal system