71 postdoc-image-processing PhD positions in Ireland-University-Ranking-2024 in Denmark
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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We hereby invite applications for one or more PhD position focusing on the development and application of hyperspectral imaging technologies for bulk forensic evidence analysis. The project aims
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of Power-to-X processes for renewable fuel production. The project is primarily rooted in process engineering while also addressing the interaction between Power-to-X plants and the electrical grid. You will
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, computer engineering, computer science, data science, mathematical engineering, robotics, or a closely related field. The candidate should have solid mathematical and analytical skills and a strong interest
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Danish health registry data, you will work with spatial data, such as disease maps and medical imaging. Such data are highly informative but also pose significant privacy risks. Your work will focus
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part of the interdisciplinary Novo Nordisk Fonden national project housed at CED, you will work in collaboration with other PhD students and a postdoc, and will have ample opportunities to interact with
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universities. The transition towards electrified and energy-efficient energy systems poses significant challenges in predicting the coupled behaviour of thermofluid, electromagnetic, and rotordynamic processes
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research has focused on optimizing materials chemistry to improve performance. Despite these advances, the fundamental processes governing electrochemical interfaces, particularly their degradation and
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or more stays at the collaborating partners in Gothenburg of a few weeks to a few months, and close collaboration with both UCPH-based and visiting PhD students and postdocs. Our group and research – and
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other relevant stakeholders. The PhD student will contribute to the prototype development, feasibility test and evaluation of innovative cross-sectoral pathways and will be involved in data collection