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; Analytical interest in and understanding of political and scientific debates in connection with climate change and global sustainability and related political processes and bodies. Hands-on experience with
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culture based on mutual respect. We are also implementing diversity-sensitive processes throughout our whole organization." Your tasks Install, administer, and troubleshoot Linux servers and applications
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 months ago
on artificial intelligence (AI), including machine learning, computer vision, and robotics. For this global organization that is pushing the boundaries of AI with cutting-edge high-performance computing, we
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to enhance the understanding of the soil-root system Find links between non-invasive geophysical monitoring and the availability of Nitrate and water in the soil Improve the small-scale process understanding
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experiment operation in 2028. Emphasis has to be put on the application of the software in real-time, making use of massive parallelism on CPU and/or on GPU. Your profile: From the applicant, we expect a
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completed application form, including any additional documents required, well in advance of the desired selection date. Applications are usually processed within four to seven months. Incomplete or inaccurate
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computer science (e.g. digital technology, chip design, computer architectures, hardware/software codesign, parallel architectures, operating systems). Innovating and improving teaching through new formats and
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are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C
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times through higher parallelization and enable targeted stimulation of hardware faults by adjusting the models. To this end, a simulation environment based on a virtual prototype will be developed using
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of inorganic ions and organic matter can cause defects in electrolyser stacks, resulting in costly process disruptions. This project considers: i) development of analytical methods for the quantification