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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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, material processing, and/or atomistic simulations is an advantage. Excellent analytical skills and proficiency in scientific programming (e.g. in python) are an advantage. Excellent oral and written
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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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, 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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at least one scientific programming environment such as Python, MATLAB, or R. Familiarity with structural degradation phenomena—including fatigue, corrosion, and biofouling—would also be beneficial
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Python (or equivalent). Experience with glass science, battery materials and/or atomistic simulations is highly advantageous. All interested candidates are encouraged to apply, regardless of their personal
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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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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Python programming skills are also required. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a
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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