446 machine-learning-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" positions in Germany
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- cellumation GmbH
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is internationally recognized for its expertise in applied electroacoustics and audio engineering, AI-based signal analysis and machine learning, and data privacy and security. Under the motto 'Where
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of learning from mistakes, with support available at any time. State-of-the-art equipment. An on-site cafeteria with daily meal options. For the preparation of the Master’s thesis, no remuneration is paid. We
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thesis will be completed by validating your simulation results. You will work on part of your tasks on site at our machine park. What you will do Researching the state of the art and the fluid dynamic
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evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric modelling is greatly beneficial. Excellent English and the willingness to learn the German language
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, efficiency, yield, and reliability. In collaboration with the Power Electronics business unit, you will acquire and manage national and international projects to strengthen the European semiconductor industry
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on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic
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practical setting. You will learn about our structures and processes in the scientific and technical business areas and be entrusted with responsible and varied tasks. Use this springboard to launch your
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for this position, the candidate should possess in-depth skills in programming and hands-on training and evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric
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/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq analysis - interest in biological applications - passion for science and