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(at least in Python and C++); ideally strong hands-on experience with ROS2. Experience in AI development, especially with neural networks. Experience with standard software development tools (Git, CI/CD, IDEs
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, CTR) Design and implement physics-informed deep neural network architectures which accelerate finding electron bunch shapes self-consistently for large measurement campaigns Implementation and
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scientific questions Proficient in scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab, SRIM/TRIM) Basic knowledge of scientific data analysis and statistical evaluation Good command
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techniques. We built pipelines based on AlphaFold and in-house developed software to predict structures of interacting proteins and in collaboration with the Steinegger lab, developed highly efficient AI-based
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knowledge of electrochemistry and experience with fuel cell test Ability to cooperate across disciplines in an international environment Independent, structured and target oriented way of working Software
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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to the availability of resources, in the context of the REACT MSCA Doctoral Network as Research Associate / PhD student (m/f/x) (You will receive a salary according to MSCA regulation, including a
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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computing, domain-specific multi- and manycore architectures, networks-on-chip (NoCs), methods and algorithms for application parallelization, simulators and virtual platforms for application- and
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) allowance for accompanying spouses and children possible travel allowance possible attendance of tailored seminars for scientific research and networking during the fellowship and beyond communication