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tumour response to treatment can then bring this much-needed clarity, and implementing this understanding into computational tools can provide the potential for rapid clinical response to patients
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seminars, workshops, and conferences of the programme. Selection Criteria For a post-doctoral researcher: a PhD in comparative political economy, political science, economics, sociology, public
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Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital
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Postdoctoral Researcher in Innovation&Investment Policy for Hydrogen Clusters in the EU(0.8-1.0 fte)
research programme GroenvermogenNL, which supports the large-scale development and implementation of green hydrogen in the Netherlands and across Europe. The programme addresses the system-wide conditions
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background and interests. Candidate Profile We are looking for candidates who meet the following criteria: PhD in a related discipline. Expertise in one of the following areas: Single-cell and spatial
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perform a prospective trial at the Dutch Breast Cancer Screening Program to determine the impact on screening performance when optimizing the radiologist’s interpretation. This trial will involve two
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Administration & Secretariat Policy & Advice IT Marketing & Communication Human Resources Finance Legal Real Estate & Facilities Management Education Research, development, innovation Academic staff PhD
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/video segmentation, object tracking, reinforcement learning. Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation
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to have the following skills and experience. We welcome applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep
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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