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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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headed by Prof. Iber, which leverages imaging data to develop data-driven, mechanistic models of biological processes. The team employs cutting-edge computational tools and imaging techniques
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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
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software frameworks Development of new signal processing algorithms (PHY/MAC) in conjunction with software-defined radio hardware Development and validation of AI/ML methods for mobile communications systems
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the developmental rules underlying phenotypic variation. The successful postdoctoral fellow will develop and implement an empirical framework that utilizes data-driven algorithms to learn relationships between past
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. This project aims to develop scalable, textile-based wearable devices for real-world joint motion tracking, enabling continuous and unobtrusive monitoring of movement in clinical, rehabilitation, and everyday
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control, machine learning, and differential geometry to work on the development of advanced algorithms to enhance the safety and robustness of human-robot interaction. The successful applicant will engage
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for a University Assistant Praedoc to join the dynamic research teams led by Assoz. Prof. Dr. Philipp Petersen, M.Sc.. The research areas developed by the team are in particular related to theoretical
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and grippers offer improved safety and adaptability but introduce new challenges in design and control. Their development is still largely bio-inspired and trial-and-error based. Integrating flight and
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Your Job: Random unitaries are a ubiquitous tool in quantum information and quantum computing, with applications in the characterization of quantum hardware, quantum algorithms, quantum cryptography