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Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills
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in medicine and other study programmes and graduate initiatives in which the Faculty of Medicine is involved is expected. Beyond the core research area, the appointee will also teach in all degree
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interfaces under reaction conditions, using machine-learned interatomic potentials (MLIPs) for automatic reaction network exploration for catalyst dynamics, and developing the next generation of kinetic Monte
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machine learning (data-driven modeling, machine-learned force fields (MLFF), structure-property relationships) for the evaluation of large data sets and to generate new research approaches. In teaching, the
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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pre-trained machine learning model for assessing cell condition based on EIS data is available from previous Master Thesis and will be integrated into the system. Here you create change literature
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting-edge Machine Learning applications
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-driven (machine learning) and model-driven techniques. As part of the DFG research project “Progressive, Spatio-Temporal Consistent Inline Activity Reconstruction and Recognition,” a doctoral position is