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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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government, administration and business in their efforts to adapt to climate change. It builds up a national and international network structure in order to integrate existing competences and knowledge, and to
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Python, for processing and interpreting complex proteomics data Familiarity with proteomics software for data analysis, visualization, and management Experience with biological samples (e.g., FFPE, plasma
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Identification of soil invertebrates (e.g. mites, springtails, insects) using modern and classical techniques Laboratory analyses of soil properties Statistical analysis of complex ecological datasets Presentation
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on Earth is a laboratory that has operated for billions of years, producing remarkably diverse, complex, and robust biological systems; however, significant challenges persist in understanding
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creative solutions for complex chemical and process engineering problem. Dehydrogenation processes: Construction of a test stand for the dehydrogenation of diol-based carrier molecules Explorative research
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio
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integration of vehicles into mobility and energy systems. We improve the efficiency, sustainability and economics of electric vehicles by optimizing and accelerating the integration of components up to complex
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together