94 post-doc-computer-graphics PhD positions at Technical University of Denmark in Denmark
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level equivalent to a two-year master's degree in Electrical Engineering, Computer Science, Robotics, Safety Engineering, or related fields. Approval and Enrolment The scholarship for the PhD degree is
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about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of applicants will be made by an academic
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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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. These are essential components for optical quantum computers and quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between
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smarter food regulation and enhance microbial food safety within Denmark’s small-scale food processing sector. You will work closely with researchers from DTU Food, DTU Compute, and DTU Management
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. Engage in interdisciplinary training to build expertise in both computational and experimental techniques. Play an active role in education and outreach in protein design and proteomics, including
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of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a
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automation Earth processing Computational fluid dynamics Numerical process modelling Rheology Furthermore, the candidate should be motivated to work collaboratively as part of a team. You must have a two-year
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analytical techniques to assess materials in both pre- and post-consumer shoes. The project aims to: Map footwear waste flows in Europe by building a database of common materials in selected footwear
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon