436 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"IFM" positions in Germany
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background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz
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for the recognition, classification and characterisation of images in a wide range of dimensions, wavelengths and resolutions. Background: In computer graphics, accurately modeling and controlling structural elements
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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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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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, 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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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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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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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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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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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