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Field
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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), machine learning algorithms, and perception methods can improve the autonomy, robustness, and precision of robotic manipulation in challenging environments. The project lies at the intersection of control
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applications to medical data. The project will combine theoretical work on multiparameter persistence with the design and implementation of algorithms for medical image analysis. The successful candidate will
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algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing extreme-scale scientific data management
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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at least one of the following fields: approximation of neural networks, convergence of Langevin/MC sampling, analysis and algorithm design of interacting particle systems, operator learning, regularity
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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on robotics and automation within the construction and built environment. The successful candidate will play a key role in developing an algorithmic solution for robotics that integrated with Building
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Job Description • Develop dynamic models and simulation frameworks for a novel pier-free telescopic coastal barrier system. • Design and implement coordinated control algorithms
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes