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- Delft University of Technology (TU Delft); Published 11 Nov ’25
- Delft University of Technology (TU Delft); yesterday published
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) for the high-luminosity phase of the LHC, in particular on its mechanical design, on the generation of the L1 trigger primitives, and on the development of offline reconstruction algorithms. In addition, it is
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with signal processing and control algorithms. Excellent communication skills in English (written and spoken); ability to work in interdisciplinary teams and to publish scientific results. A strong
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opportunity to choose between two missions: • Mission 1: Improve new automated algorithmic schemes to quickly, efficiently and robustly detect and extract recorded geophysical signals related to earthquakes
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members Participate in traffic scenario generation project and pedestrian modeling project. Develop sophisticated AI-driven algorithms that create realistic, safety-critical test scenarios for autonomous
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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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SD-26065 -POST-DOC IN METHOD DEVELOPMENT FOR HIGH RESOLUTION CHARACTERIZATION OF NOVEL SAFE AND S...
methodologies and algorithms for image fusion and co-registration Experience in writing, first authoring of publications and reports Interest in setting-up new academic and industrial collaborations Interest
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, and improve prediction accuracy - develop Machine Learning and AI algorithms for crop management, yield predictions and decision support systems - prepare manuscripts for peer-reviewed publications
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation
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, chemical fixation and resin embedding, FIB milling, cryo preparation) Experience in developing and using correlative workflows, data processing and data visualisation, including methodologies and algorithms
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for the design and the benchmarking of algorithms tailored for photonic quantum computation. The outcome of the project will be the assembling of three prototypes: ● QSPACE, machine encoded in spatial modes and