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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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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python
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analysis. Experience with programming tools like Python and energy system modelling tools like PYPSA is considered an advantage. The successful candidate should possess a curious and interdisciplinary
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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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experiments Desirable: • Backend development (Python, Ruby, …) • Linux system administration (deployment, networking) • Experience with decentralized/self-hosted services, e.g. Mastodon, Nextcloud, Matrix
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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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with Robotics Excellent programmer in Java / C / Python / ROS or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical
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biology, pharmacology and/or immunology. Experience in statistical bioinformatics, including developing analysis pipelines and applying programming (R/Python) to genomic/transcriptomic data. Strong written
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, optimization, control, probability/statistics, game theory, mechanism design, or machine learning (at least one) Programming experience (e.g., Python, Julia) Strong analytical thinking and problem-solving
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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