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real-time during behavioural tasks Integrating virtual reality paradigms with behaviour and imaging to assess decision-making processes Exploring potential therapeutic interventions for NMDA receptor
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to process and understand large experimental datasets (e.g., image processing) #analyzing experimental results; developing conceptual models and parameterizations #scientific publication and presentation
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Studying lipid alterations of tumorous material by mass spectrometry imaging Quantification of corresponding lipids using liquid chromatography mass spectrometry Data analysis of sequencing and microscopy
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DTU Tenure Track Researcher in X-Ray Nano-Computed Tomography for Dynamic Processes in Geological...
computed tomography (CT) imaging of dynamic processes Thorough knowledge and understanding of different nano-CT beamlines, their usage and limitations for in-situ imaging Image segmentation and pore-network
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to biological data sets such as omics data, protein structure prediction, or biomedical imaging. Technical experience in programming (Python preferred), and/or machine learning is a plus—not a requirement. We
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-inspired data and image analysis, often in close collaboration with experimental partners, to identify physical principles behind biological dynamics and self-organization. The project: Voluntary motion in
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, cardiovascular disease, and developmental disorders. 2. Mitochondrial responses to hypoxia Evidence indicates that mitochondria respond rapidly to hypoxia, controlling systemic processes in the vasculature and
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location in Dortmund, we invite applications for a PhD Candidate (m/f/d): Mass Spectrometry Imaging The position is to be filled within the framework of the EU-funded project European doctorial network
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causative treatment in the patients. Work will employ genetic tools, manual and automated patch-clamp measurements, immunohistochemistry, confocal/STED imaging, light-sheet fluorescence microscopy, and
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: Programming in Python and/or R Data science (e.g., tidyverse, pandas) Machine learning (e.g., scikit-learn) Deep learning (e.g., PyTorch, Keras3) (Optional) bio-signal processing and brain imaging (e.g., EEG