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19.04.2024, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Computer Engineering at TUM has open positions for a doctoral researcher (TV-L E13 100%, 3-4 years
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specificity. Despite progress in the temporary suppression of chronic inflammatory diseases, they still fail to be curative. This project aims to address this unmet medical need by generating fundamental
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Violence against Women in India (ECOVI)”. This position: The Professorship for Global Health is situated at the TUM School of Social Sciences and Technology (Department of Governance) at the Technical
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23.04.2024, Wissenschaftliches Personal We are offering one PhD position to a highly motivated student focusing on the interconnections between biophonic and anthrophonic sounds and environmental features with an emphasis on vegetation complexity, urban infrastructure, and bird diversity. The...
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15.05.2024, Wissenschaftliches Personal The EQUA Endowed Chair for Family Business Culture and Ownership at TUM School of Management is offering a PhD position on the broad topics of responsibility and branding, which can be tailored to the individual research interests and expertise of the...
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for clinical use. The Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM) and the Institute of Biological and Medical Imaging (IBMI) at Helmholtz Munich are an integrated, multi
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information flow. Understanding these attributes is critical for the responsible application of such models to medical settings. Your Qualifications: - Holding an excellent MSc in the field of pure or applied
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matter physics, biomedical/material engineering or a related discipline. You have a strong background in data analysis and image processing. You enjoy working in interdisciplinary and international teams
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or comparable degree in physics, biology, bioengineering, material engineering or a related discipline. You have experimental experience in cell/tissue culture, microfluidics, or a related discipline. You enjoy
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models