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the theoretical and algorithmic foundations of AI. A strong commitment to excellence in undergraduate and graduate teaching and mentorship is essential. Preference will be given to candidates who show promise in
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development of algorithms and large-scale numerical simulations. Your expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and
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: graph neural networks, natural language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance
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sciences, who ad- dress key issues in AI such as reproducibility, safety, trustworthiness and robustness, and who engage with the theoretical and algorithmic foundations of AI. A strong commitment to
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interdisciplinary work, for example in medicine or life sciences, who address key issues in AI such as reproducibility, safety, trustworthiness and robustness, and who engage with the theoretical and algorithmic
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
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utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project (www.timberhaus.eu). Your tasks Develop machine learning models and computer vision algorithms for wood
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are particularly interested in candidates working on quantum error correction, algorithms, simulation and qubit architectures. We are also interested in outstanding scientists in theoretical quantum computing in a
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language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance, financial networks, e-democracy, voting, social
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has been created in theoretical quantum computing. We are particularly interested in candidates working on quantum error correction, algorithms, simulation and qubit architectures. We are also