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approaches for the analysis of omics, digital, and molecular pathology data, to support precision medicine. We work with real-world data in a highly interdisciplinary environment fostering translational
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position at a leading technical university that generates knowledge and skills for a sustainable future Engaged and ambitious colleagues along with a creative, international and dynamic working environment
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of PhD students in the project Profile We are seeking highly motivated candidates with strong achievements and a proven track record. Applicants must have: A PhD in physics, chemistry, materials science
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teaching load of 2 classes per year. The position is for two years, and can be renewed for a third year pending satisfactory performance. Required Qualifications ● A PhD in Mathematics or an equivalent area
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project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
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. These posts are suitable for newly qualified PhD's in areas such as health professions’ education, sustainability education, health services research, public health, psychology, sociology, etc. Experience
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taken into consideration. A suitable candidate will have a PhD in sociology, computer science, economics, statistics, political science or a corresponding subject of relevance to computational social
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Creating and validating digital twin architectures that incorporate physical laws and constraints Applying digital twin technology to ITS applications such as traffic management, vehicle routing, and
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. Strategic management of platforms and innovation ecosystems – open innovation, platform orchestration, and multi-stakeholder partnerships in dynamic environments Strategic use of intellectual assets and data
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. Neil Sinclair and Prof. Marko Lončar), where TFLN devices will be fabricated at DTU and TFLT at Harvard. Scientific Environment The project is funded by The Novo Nordisk Foundation and anchored at DTU