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Algorithm-HW-Codesign for wireless signal processing investigate novel hybrid imaging and coded excitation approaches for medical ultrasound reliable and resilient communications for critical applications in
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially
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for technologies Conscientiousness in implementing, testing, and documenting algorithms Curiosity about a deeper understanding of deep Learning architectures Experience in academic writing is an advantage What you
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analysis tools Implementing continuous benchmarking of the library Optimization of the library algorithms and underlying data models for speed and memory efficiency Maintenance and improvement
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, and documenting algorithms High degree of proficiency in spoken and written English What you can expect Fascinating challenges in a scientific and entrepreneurial setting Attractive salary Modern and
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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to their spin properties. What you will do You will program the connection of quantum experiments to an existing HPC system for the external execution of quantum algorithms. You will develop an efficient user
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s