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, or Python. You will also be able to shape your own research. This includes primary data collection through surveys, or qualitative or quantitative interviews. Working as a PhD student requires the ability
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knowledge and skills in machine learning - Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the
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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C
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design for resource allocation or distributed systems Solid mathematical and analytical skills. Experience in scientific programming (e.g., Python, MATLAB, or similar). Demonstrated ability to publish
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information theory. Experience in programming, e.g., in C++, Python or with quantum simulators, such as NetSquid, is a plus. Familiarity with the concepts of quantum information and quantum computing. Curiosity
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Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) • Strong programming skills (e.g., Python) • Strong skills in machine learning, deep learning and modern
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. Experience with digital twin modelling and validation of energy system solutions will be an advantage. Strong programming skills in Python, MATLAB or similar environments are required, and it will be advantage
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, Grasshopper, Python). Explore new trajectories for the advancement of AI-supported integrated architecture and its potential impact on the build environment. Contribute to developing open-source tools and code
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, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity to work with researchers from a heterogeneous group, with core expertise in communication theory, networking, information theory, statistics
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the interdisciplinary lab to bridge environmental concerns and creative design processes. • Investigate the creative process at the intersection of LCA, AI, and early design phases. • Merge Python-based approaches