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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 2 months ago
. Numerical methods, in particular FEM-based stress analysis at initiation sites within the framework of local fracture approaches, provide a natural bridge between experiment and mechanistic understanding
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successful candidate will hold a PhD degree in Computer Science / Engineering, Electronic Engineering or a closely related discipline, with a good track record of original research publications. The successful
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network architecture design and optimisation. It is envisaged that the candidates will be located at University College Cork’s campus. A successful candidate will hold a PhD degree in Computer
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that want to get their hands onto a real mission and bring a contribution to society. You also have: A PhD in engineering (aerospace engineering, electronics or related fields) You have proven experience in
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Are you passionate about experimental aerodynamics and flow visualization? Apply for a PhD position that aims at transforming flow field measurements into aerodynamic forces by pressure and friction
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physical vapour deposition, and associated patterning techniques. The project aims to deliver step-changes in imaging resolution and enable functional imaging capabilities, such as probing local
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. Job requirements We look forward to dynamic candidates that want to get their hands onto a real mission and bring a contribution to society. You also have: A PhD in engineering (aerospace engineering
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: ). Your profile Core qualifications: A PhD in computer science, medical informatics, computational biology, bioinformatics, or a related field, with an interest in biomedical informatics and translational
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Science, Technology and Higher Education”, under the following conditions: 1. Scientific Area: Molecular Biology 2. Admission Requirements: 1) PhD in Molecular Biology, Genomics, or related fields
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(e.g., walking, cycling) related physical activity; finetuning, evaluating, and improving model performance using local data and ensuring explainability, fairness, and robustness of the model outputs