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Postdoctoral Researcher in Semantic Knowledge Engineering & Interoperability in Materials Science in
, navigation, and visualization concepts for research data infrastructures based on the developed knowledge models Design and implementation of dissemination, training, and community activities to establish
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distinct NR2F1 dosages to study their effects across neuronal differentiation. By integrating time-resolved bulk (RNA-seq, ATAC-seq, ChIP-seq, Hi-C) obtained from neuronal lineages cultured in 2D cells and
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, and safety glasses · Visual acuity for microscopy and detailed sample observation · Occasional animal handling (mice) may be required · Occasional evening or weekend work may be necessary depending
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experimental workflows Specific Requirements Experience in Python or similar tools for data analysis, visualization, and automation would be an advantage, especially for handling large experimental datasets and
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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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negotiated with the successful candidate. The maximum appointment is two years. Research projects for the Postdoctoral Associate will be generated in any of the following ways: 1) an issue of importance in
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using cell lines according to ISO-10993 norm. In vitro visualization methods, staining (CLSM) Evaluate antibacterial activity under physiologically relevant conditions (serum proteins, pH changes
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, navigation and control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line
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the PI in writing scientific papers based on research findings that includes generating graphs, tables, and other visuals for internal reports, grant applications, and publications. Collaborates with other
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and validate a novel single-camera markerless motion capture system, combining biomechanical realism, synthetic data generation, and privacy-preserving visualization within a single framework, to enable