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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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, ability to work independently and in a team. Choose Duke How to apply: Candidates with a PhD, MD or MD-PhD degree and a minimum of one first author publication should send their CV, a brief letter of
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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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 Distributed machine learning takes advantage of communication and
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your skills in over 600 courses
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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, but if you are ambitious and successful, there are plenty of opportunities to connect you to all relevant top research groups in the world in quantum information, quantum technologies and machine
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representations of time‑dependent data through sequences of iterated integrals and have recently gained significant attention in machine learning and data science. The project will investigate how
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shelf lives, and additionally may change colour, texture, and stiffness rapidly. Further, the lack of standardised 3D models for the wide variety of products makes offline learning challenging. As a