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, CSF) or advanced proteomics workflows (e.g. spatial proteomics) Fluent with proteomics data analysis tools and data management, programing skills in R’ or Python highly desirable Service-oriented
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, independent working style Experience in Computer Vision The weekly working time is 10-20 hours. The position is initially limited to three months, an extension is intended. We value and promote the diversity
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skills Physical presence in our labs Strong knowledge in mathematics and linear algebra Proficient English skills Precise, responsible, independent working style Experience in Computer Vision Experience in
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performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take
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of Pu in both solution and solid phases using advanced spectroscopic and analytical techniques. - Analyze and interpret spectroscopic data to understand Pu behavior in carbonate-rich environments
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analyzers, spatial/imaging coming in now) Consult users in experimental design and data interpretation Train users for independent equipment and software usage Liaise with external customers and service
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. Qualified female candidates are especially invited to apply. Persons with severe disabilities will be given preference if they are equally qualified. Information on job advertisements and the collection
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Kunsthistorisches Institut in Florenz - Max Planck Institute, Florence, Italy | Germany | about 1 month ago
local communities faced urgent technical challenges, some from the past, such as moving ships, and others that were important in the past and remain so today, such as the supply of water. More information
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knowledge of working in laboratories, with scientific equipment, and in digital data processing. You are motivated to learn how to control modern technologies, methods, and processes in the field of optical
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial