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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding algorithms, or demonstrated ability and
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design
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performance. Some suggested research topics may include: (i) NISQ algorithms, (ii) quantum simulation of complex many-body systems, and (iii) quantum computational complexity. This list is not intended to be
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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the study of problems in quantum many-body physics through the lens of quantum information and quantum computing? Do you enjoy analyzing complex quantum mechanical systems through a combination of
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, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling
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learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems