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. Activities include ultrafast quantum physics, quantum technology with rare earth atoms, quantum states in nanosystems, quantum information theory, quantum spectroscopy, quantum algorithms for optimization
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includes implementing and testing machine learning algorithms on quantum control tasks such as state preparation and qubit reset. You will gain hands-on experience with machine learning techniques and their
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Doctoral student in development of nanowire devices for photonic neuromorphic computing (PA2026/472)
dynamic photonic sensor array with on-chip neuromorphic intelligence. This is enabled by significantly advancing the state of the art in optoelectronic algorithm-hardware co-design and multi-scale
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as
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Computer Vision algorithms. Experience using urban building stock modelling and urban digital twins What you will do: Design & Develop: Create data structures for detailed, spatialised construction component
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
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alternative ways of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test
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dimensions andanalyse particle trajectories using a combination of established tracking algorithms and machine-learning-based approaches. You will further correlate the diffusive behaviour of viruses
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for fast tune-up Implementation and benchmarking of quantum algorithms Qualifications We are seeking candidates with: A PhD in Physics, Applied Physics, Nanotechnology, Computer Science, Engineering, or a
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systems. However, when dynamics are complex, nonlinear and partially unknown, such a model is typically obtained from observations by performing system identification. Typical identification algorithms