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topologies (sampling problem) and angular estimation algorithms (estimation problem) is required, while considering the physical effects (EM problem). The novel idea in DoAnt is to develop an EM-driven
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. In your role as a PhD candidate, you will: Engage in ground-breaking research to develop new concepts and theories; Synthesise social science research methods and systems thinking to study projects
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thorough understanding of this complex and continuously changing reality is crucial. As a PhD candidate at TU Delft, you will develop dynamic systems models to capture these developments and uncertainties
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to visualize complex fiber networks. Your task will be to analyze measured scattering signals from different biological tissues, develop enhanced image processing tools to improve the reconstruction
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systems such as mobile manipulators, quadrupeds, and drones, and deploy them in complex real-world environments. We are looking for an enthusiastic and open team player to help us develop the next
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other sensors, such as radar or microphones. In addition, you will develop and test machine learning algorithms that can track people and objects, such as cars, using the input from cameras and sensors
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, collaborative, and friendly atmosphere, we will give you all the support you need to develop and grow. Become part of an expansive ecosystem shaping the development of 6G. You will benefit from training in 5G and
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atmosphere, we will give you all the support you need to develop and grow. Moreover, as a valued member of the FNS consortium, you can collaborate closely with various partners in pursuit of integrating
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Sustainable Development Goal #6 ‘clean water and sanitation’ as well as forecasting impacts on one of the Planetary Boundaries, namely ‘land-system change’. Key Responsibilities: Develop a multi-scale GIS-based
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programming (Python and/or Matlab). Good interpersonal and communications skills. Prior experience in AI/machine learning is a plus. Affinity for biomedical imaging is a plus. Motivation for teaching and