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Field
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, productivity, and overall operational stability of the process plants can be determined. This rigorous analysis will provide a clear picture of the flexibility potential and set the stage for implementing
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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processes. In this project, we will leverage the advanced voltage imaging in larval zebrafish to investigate how intrinsic plasticity reshapes neuronal behavior. Your job Traditional electrophysiological
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doctoral student who has Competence and skills: -Strong foundation in computer vision (e.g., object detection, image segmentation) and NLP (e.g., text reasoning, language models). -Knowledge of generative AI
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maximum of ONE student per project. This process will ensure an excellent fit of student to project and also an excellent strategic fit of the project within the faculty. Project titles: Bayesian methods
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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of dynamic processes to address global challenges, from mitigating the impacts of natural hazards and sustaining our habitat amid global change to responsibly managing georesources. We are part of
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process (process-specific design) (2) Optimization of the LPBF process parameters to achieve desired microstructure and material properties, (3) In-depth materials, and property testing and (4) Prototype
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Biology and Biomedicine - in the lab, in the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors
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–plant interactions. Your main responsibilities will include: Developing and applying high-resolution time-lapse GPR and EMI imaging methods at multiple scales to enhance our understanding of the soil–root