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Your Job: The accelerated development of advanced materials is essential for addressing major challenges in energy, mobility, and sustainability. Traditional trial-and-error methods in materials
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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dynamics or Hamiltonian eigenstates with classical and quantum algorithms Comparison of quantum algorithms with classical baselines Analysis and documentation of results What you bring to the table Student
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for autonomous systems. Our focus lies on safety-critical applications in the fields of automation, mobility and health. We develop reliable software technologies with a benefit for humans. For example, we conduct
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system development and software development for four scientific laboratories Measuring devices and data analysis • InSAR (Interferometry of Synthetic Aperture Radar) computing system • IR mass spectrometer
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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algorithms for very high speed coherent passive optical networks (VHSP) Implementation of DSP algorithms in MATLAB/C++, that can be used for ASIC development Development of our DSP software tools Research work
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enable the digitisation of strategies for the expert. The concept is also used to describe an algorithm for the development of process parameters to eliminate laser-induced roughness during laser polishing
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algorithms and Quantum Imaginary Time Evolution. What you bring to the table Experience with Python programming Experience in programming quantum algorithms with Qiskit, Pennylane, or similar Prior knowledge
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project within the SusMax network focused on developing interpretable machine-learning frameworks for kinetic multiphase reaction-network discovery in the catalytic conversion of renewable feedstocks