89 algorithm-development-"Helmholtz-Zentrum-Geesthacht" PhD positions at Technical University of Denmark in Denmark
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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on the reactivation of cement and optimizing the cement blend. During the PhD study, the reactivity of recycled cement and thereby the strength development is optimized by the chemical elements that are missing in
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
three years emphasizing the development and testing of next-generation serious gaming approaches with respect to construction safety, health, and well-being or emergency response applications. This PhD
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impact.´ Job Content, Responsibilities, Tasks, and Qualifications Your overall focus will be to develop and apply novel bioinformatics methods that reduce bias and improve the accuracy of genomic analyses
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biomaterial-based drug delivery. The position is part of a larger interdisciplinary research initiative aiming to develop targeted therapies for osteoarthritis (OA) by combining antisense oligonucleotide (ASO
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qualifications The overall objective of this project is to upcycle excess earth from construction sites into sustainable structures. This will be achieved through the development of advanced, automated processes
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design to develop new high-potential organic flow battery electrolytes with unprecedented stability. The computational work will be done in close collaboration with an experimental counterpart