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Field
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interoperable methodological framework for AI in gynecological oncology. Your tasks: You will contribute to the development of explainable AI systems and the core methodological framework: Contribute
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description: Spatial interactions are key processes for the development and maintenance of multicellular systems. Disturbances in interactions lead to developmental disorders or diseases. In many cases
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
Integration in the doctoral training network “Digitalization” Access to high-quality training and professional development opportunities on digitalization topics, including programming, research data management
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international level Excellent opportunities for professional development and access to state-of-the-art technologies via the University of Münster campus Flexible working hours Contact: Dr. rer. nat. Insa Buers
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for emerging material characterization. Core questions will be how structural motifs control ultrafast excitation dynamics and coherent electronic state evolution in chiral organic molecular semiconductors
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plant breeding. More than 30 research groups study regulatory networks controlling fundamental traits such as reproductive development, organ geometry and growth, innate immunity and microbiome effects
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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 2 months ago
Interactions” to develop datasets and algorithms to capture and analyze eye gaze. About the project We are supporting the development of highly realistic human and animal avatars for use in research, film
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. The flexible dye laser systems require hands-on work in optics (spectroscopy, laser physics) and software development. Data evaluation is an essential part of the project work to distinguish between
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. Within the framework of an interdisciplinary collaborative project, we are working on the development and investigation of novel refractory high-entropy alloys (HEAs) as potential candidate materials
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)Informatics/Data Science or related disciplines is desirable. The positions focus on the development and application of new methods to predict multi-omic traits and phenotypes from large genetic datasets. More