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Field
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electricity/electronics, chemistry, and optics, as you will be working with advanced custom instrumentation. Experience with programming (for example Python/Matlab) and image analysis is highly recommended
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to conduct safe experiments. Experience with optical measurement techniques. Good programming and data analysis skills (e.g., Python, MATLAB, LabVIEW). You must meet the requirements for admission
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design processes from RTL to GDSII ideally, experience in using Design-Flow-Tools (i.e. Xcelium, Genus, Innovus) and script languages (especially Python) and AI frameworks (i.e. TensorFlow, PyTorch
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, transforms, optimization). Programming and simulation experience (for example MATLAB, Python). Strong written and oral communication skills in English. Ability to work independently and in teams. Curious
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measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Practical laboratory skills and an enthusiasm for experimental work are highly
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skills in Python and/or R; experience with Linux/HPC environments is an advantage Experience with genomic data analysis, high-performance computing, GPU programming, or software development is a plus
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong
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effective collaboration, particularly during measurement campaigns at synchrotron and neutron facilities. Experience with programming languages such as Python is advantageous. Participation in teaching
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skills (mandatory): Strong understanding of sustainable AI or related areas Experience of programming in Python / C / Java or equivalent Experience with using Machine Learning software, e.g. PyTorch
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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