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Field
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learning-assisted computational pipeline for the automated detection of point defects in atomic-resolution scanning transmission electron microscopy (STEM) images. Using monolayer MoS₂ as a model system, the
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, prototype and evaluate novel rehabilitation technologies including wearable, neural interface and robotic systems contribute to competitive grant applications, ethics submissions and project reporting publish
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-Talisman Lab, please click here . As a successful candidate, you will: Purify EVs from cultured cells and plasma using different analytical platforms. Perform imaging experiments using super-resolution
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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to: Contribute to development and deployment of particle imaging systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis
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, working closely with other project participants on field measurements, laboratory work and model development. The candidate will be expected to: Contribute to development and deployment of particle imaging
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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Job Code: 21/2026 Job Offer from June 26, 2026 At the Max Planck Institute for Human Development, we study how and why people develop differently over the course of their lives, and how physical
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and develop the corresponding biasing network.; • Fabricate and assemble a proof-of-concept prototype on a glass substrate.; • Experimentally characterize the electromagnetic performance
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mechanisms in order to provide fundamental insights into endothelial ageing and pave the way for interventions that target microvascular health to promote healthy ageing. Advanced microscopy and imaging