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of methodologies for analysis and visualization of time-dependent data. Research and development of methodologies for analysis and processing of geometry data, e.g., technical plans or 2D/3D CAD objects. Evaluation
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of the following areas: Optics and microscopy, including experimental setup design and assay development Data analysis and programming, preferably using MATLAB or Python Experience in microfluidics and
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and spectroscopic data Development, implementation and application of methods for the analysis of data on dwarf galaxies Contributions to international collaborations (especially Euclid and ARRAKIHS
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, Neuroscience, or a related field. Candidates should have strong skills in statistics. Programming skills (e.g., Python) and experience with PET or MRI imaging and data analysis are desirable. Furthermore
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equivalent) in Psychology, Neuroscience, or a related field. Candidates should have strong skills in statistics. Programming skills (e.g., Python) and experience with PET or MRI imaging and data analysis
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Developmental Biology. Our research focuses on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative
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focuses on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative colleagues who share a common interest
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analysis tools – including digital twins, forecasting systems, load flow analysis, and transient simulations – to design an innovative planning and operational concepts for future power systems, such as grid
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research focuses on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative colleagues who share a common
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 13 days ago
multimodal Visual Foundation Model for arthritis that integrates imaging, clinical and laboratory data. Advance methods for explainability, domain robustness and federated or privacy-preserving analysis