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Your Job: In this Master’s thesis, you will investigate the impact of different programming algorithms on the stability of resistance states using a sophisticated 3D Kinetic Monte Carlo (KMC) model
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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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, 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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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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innovation journey! What you will do Project and research work in the field of microwave photonics Electromagnetic simulation of circuits, antennas, filters, and related structures Characterization of high
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learning and 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
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algorithms in the field of welding technology. Joining three different metal sheets using resistance spot welding (RSW) presents researchers with challenges. We are tackling these as part of a public research
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do In our Trustworthy Digital Health group