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integrate large-scale sequence and RNA-seq data from internal and public resources. You build a reference library of predictive regulatory motifs. You use network analysis and random-forest approaches
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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European sea basins over decadal timescales, due to coastal darkening (COD) and artificial light at night (ALAN), and will determine drivers, sources and impacts of these changes at both large and small
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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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at large scale facilities Establishment of cooperation projects with energy-related institutes at Forschungszentrum Jülich Initiating grant applications Supervision of MSc and BSc students Presentation
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models using experimental data for precise mapping of real processes Conducting detailed analyses of thermomechanical stresses in electrochemical converters using the finite element method (FEM
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important insights into clinically relevant aspects of cancer development and therapy Perform state-of-the-art in vivo experiments and large-scale drug and genetic screens Learn and apply a wide spectrum of
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of a project with limited experimental data points? In addition, how would you combine various computational chemistry methods that can leverage data to enhance potency predictions? With your solution
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, economics, business informatics, data science, or a related field, • with a strong passion for entrepreneurship and/or family enterprise research, • with a solid knowledge of empirical research methods