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Field
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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. While the chosen design has a significant effect on the most important aspects of users’ experience, the algorithms, and thus the supply decisions, are based on users’ preferences. This PhD position
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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Collider? We look forward to your application! As a PhD candidate, you will conduct fundamental research in experimental particle physics, perform data analysis and develop object reconstruction algorithms
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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developing 3D vision algorithms for object detection, recognition, and scene understanding to support planning and task execution in dynamic environments. Publishing research findings in leading international
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validating a machine learning prediction model for CP and related outcomes using neonatal MRI, EEG, GMA, HINE, and clinical data. Coordinating patient inclusion, data collection, and analysis across multiple
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wing panels. Reliable process control is critical: underheating leads to poor bonding, while overheating causes polymer degradation. At the heart of process control algorithms lies a physics-based
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algorithms for: Swine production: Early detection of health problems in pigs (respiratory diseases, abnormal behaviors) from video streams. Swine processing: Automated assessment of animal condition and