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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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. You have a strong ability to solve problems and formulate algorithms. You also have an interest in genetics and genomics. You are organized, proactive, and can work independently as
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the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software
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, use imitation learning algorithms to learn pick-and-place actions, design HRI experiments with users, evaluate data, and share the code and benchmarks in open repositories. This postdoctoral position is
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, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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languages such as Python, C++, or Julia Demonstrated experience in the development of hardware-accelerated scientific applications and high-performance distributed computing Commitment to the best practices
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate