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Field
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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Types Using Machine Learning Based on Citizen Science Audio Recordings and Satellite Imagery” (Bio-O-Ton-2). Our overarching goal is to develop and test novel machine-learning approaches for combining
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possible to train a machine learning model to identify tumor-reactive T cells infiltrating any tumor type, cutting months off the time it takes to develop personalized cell therapies for patients. We
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
carbon deposits more effectively, serving as a vital tool for their management. Your Tasks Evaluate how the proposed ensemble machine learning model compares to traditional radiative transfer models and
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materials science, physics, chemistry, electrical engineering (or a similar discipline) with focus on sensorics; experience in data processing and machine learning; experience in 2D materials synthesis and
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-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this project, we highly
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2019, unites top PhD students in all areas of data-driven research and technology, including scalable storage, stream processing, data cleaning, machine learning and deep learning, text processing, data
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is currently the main focus. Here, laboratory experiments are usually combined with state-of-the-art methods such as optogenetics, connectomics or machine learning. Activate map To activate the map
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defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
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parameter space of the electrolysis processes. DoE is required for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map