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Doctoral candidate (PhD) – Computational Biomedicine / Machine Learning / Spatial Omics (m/f/d) Stellenanzeige merken Stellenanzeige teilen starting 01.09.2024 at the Institute for Computational
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machine learning-based software applications for materials science Develop code and utilize machine learning to support the automation of characterization and fabrication processes Ensure the integration
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Phenotyping” offers a position from 01.03.2024 as PhD student (m/f/x) for development and implementation of machine learning applications and data analysis in Translational Psychiatry Kennziffer: 8740. Your
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the benefit of research advances for the patients by way of a close and innovative networking of basic research-oriented and clinical neuroscience. The Project Group “Translational Machine Learning” offers a
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scattering and runs a specialized subgroup on machine learning (artificial intelligence and deep learning) for the analysis and prediction of experimental scattering data. Currently, there are several options
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/software co-design and operating/runtime systems. Typical application domains are e.g., signal-/image processing, machine learning and control algorithms for robotics. Tasks: research and development in
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multidisciplinary environment, the candidate will work on the development of novel methods for analysis of state-of-the-art spatially resolved data. The candidate will explore the landscape of explainable machine
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application domains are e.g., signal-/image processing and machine learning. Tasks: scientific research and development in designing and programming fied programmable gate arrays (FPGAs) for accelerating signal
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at the Institute of Human Genetics, in the workgroup "Regulatory Genomics" of Prof. Martin Kircher. The bioinformatics group performs research in the fields of sequence analysis, data mining, machine learning and
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to the FAIR-ification of data, establishing systematic data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s