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Field
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Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
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and signal processing methods using machine learning techniques to enhance the resilience, efficiency, and security of cell-free massive MIMO systems, which are expected to play a key role in next
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for the accurate calculation of materials properties. You will combine methods from quantum informatics and solid-state physics to describe the complex electronic and ionic processes in battery materials. New
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and digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods
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on developing a fundamental understanding and numerical models for multiphase flows, which are crucial for various industrial processes. The successful candidate will develop advanced physics-based methods in
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. This will include a detailed assessment of existing methods to address such risks, and on how to achieve a better use and exchange of existing protocols and data. The project includes the use of Digital Twins
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research in information and digital technologies (computer science, automation, robotics, artificial intelligence), with the aim of developing methods for representation, analysis, and control of complex
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and digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods
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-3413 ), 4-Limited flight data for adaptive methods (doi.org/10.1016/j.geits.2022.100028 ), and 5- Failure to use a robust state estimator to increase robustness of EMS in eVTOL, have not been filled by
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issues such as privacy, security, and bias in digital health systems. You will adopt a mixed-methods approach, combining qualitative and participatory methods to map the needs of healthcare professionals