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among research groups Establishing mechanisms to gather input, needs, and feedback from community members Managing the ETH Zurich side of the Joint Doctoral Program on Learning Sciences (JDPLS ), and
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for global society and future generations. A tailor-made program for your professional development. Participation in and shaping a dynamic research team with supportive colleagues, fostering collaboration and
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the SVT course programme Contributing to the operation of the group and the Institute Profile You ideally have a Master’s degree in computer science, artificial intelligence, transportation engineering, or
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have a Bachelor’s or Master’s degree (any field of study is welcome - computer science is not a must-have) or can demonstrate equivalent knowledge and experience You are passionate about analyzing
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. Profile You hold a Master's degree in a relevant field such as data science, computer science, physics, computational biology, or biomedical research. You are proficient in Python programming, with
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Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by
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Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by
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informatics in rehabilitation, particularly in the development and implementation of digital solutions to support patient care, is advantageous, as is the ability to directly link scientific findings with
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, computer engineering and/or computer science towards producing relevant and impactful health-monitoring mobile/wearable solutions, then please apply. The research will be highly collaborative; you should be
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Theory, Queuing Theory, Age of Information), Network Calculus, Graph Theory, Convex and Non-convex Optimization, Approximation Algorithms. An excellent Master’s degree in Computer Science, Engineering