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, working closely with AI specialists and data scientists. Methodologically, you will explore advanced deep learning approaches, including convolutional and transformer-based architectures, as well as methods
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-based, probabilistic, and in-memory computing, are based on a wide variety of physical processes, materials, architectures, and algorithms. For effective implementation, these aspects need to be mapped
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding Tenure Track PhD EngD Working as a UT student
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will include qualitative interviews and scenario workshops. The position is embedded in the HySuccess project that is part of the national research and innovation programme Groenvermogen. In addition
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transformation of energy systems and industry sectors, contributing to mitigating climate change. In the Netherlands, policy, industry and academia are working in the national Groenvermogen programme towards
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, including grades. Your PhD thesis. Starting date of the position: flexible, currently aimed to start around February 2026. For more information regarding this position, you are welcome to contact Dr. Silke
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, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research
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, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.
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: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical
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learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques Translating deep learning models into clinical settings