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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical systems theory Excellent analytical and problem-solving skills Desirable criteria Advanced programming and data analysis
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leverage advanced bespoke continuum robotic systems to demonstrate the feasibility of applying the proposed coatings can be deployed in-situ. Ultimately, this work bridges the gap between the theory
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. Ultimately, this work bridges the gap between the theory of advanced material science and the challenges of implementation in an industrial environment. This research contributes to advance the fundamental
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interest in social theory to join the workstream ‘Co-creating Concepts of Care.’ The expectation of the successful candidate is twofold: 1) To co-develop and conduct their own PhD project on how racialized
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-economics. Experience in working with datasets and prior coursework in probability theory and statistics will be helpful, but not necessary to apply for the position. How to apply: Please choose Electrical
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Modulo Theories) solver. The work aims to demonstrate methodology through the application of the prototype to a real-world industrial system (provided by our industrial partner - Evolution Measurement
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Theoretical Quantum Materials We invite applications for a PhD position in theory of quantum materials at Aalto University, Department of Applied Physics. The position is part of the FUN-VAN Research Council
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-based symbolic machine learning. The aim is to give the industrial widely used NewWave theory (a theory that predicts the linear shape of extreme waves) a modern twist to account for the important