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networks, online analysis with delay, and theory of distributed algorithms. Job description In our group, we try to apply and unite the approaches and techniques of theory and practice. Some members of our
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methods that can adapt to changing external conditions and continuously learn from data in a distributed way. Coupling of new theory with effective implementation strategies have the potential to make a
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continuously learn from data in a distributed way. Coupling of new theory with effective implementation strategies have the potential to make a lasting impact on building efficiency through sustainable
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responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling, or generative modeling. Collaborating with
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postdoctoral researcher, your responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling
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, financial networks, e-democracy, voting, social networks, online analysis with delay, and theory of distributed algorithms. In our group, we work on both theory and practice: some members of our group focus
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institutions, to build a framework for discovering, sharing and executing data and algorithms in a distributed environment. The main technology will be Python, though Scala and Typescript knowledge are a plus
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for monitoring people’s health. You will focus on developing new solutions, electronics, algorithms and methods to assist individuals, physicians and sports coaches to effortlessly and continuously monitor health