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Field
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an experimental aerodynamics team has concentrated on the development of advanced non-intrusive measurement techniques such as Particle Image Velocimetry, InfraRed Thermography and Background Oriented Schlieren
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) at Argonne National Laboratory to advance learning-enabled imaging methods. This position offers a unique opportunity for candidates with backgrounds in electrical engineering, computer science, applied
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-based composites using melt electrowriting printing, support for PhD students working with 3D extrusion-based and 3D liquid-in-liquid printing, testing of MOFs for dissolved CO2 capture, investigation
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of world-renowned researchers and educators have access to a state-of-the art core facilities and expertise, including for high-throughput screening, multimodality in vivo imaging, proteomics, integrative
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spatial resolution and implement quantitative phase imaging to enable 3D imaging and calibration-free mass concentration mapping. The fellowship holder will then have the opportunity to investigate
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deliver a prototype of a 3D-printed or casted bioactive stent with proven tissue compatibility and mechanical stability, paving the way for improved cardiovascular implants. The Opus LAP project includes
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
translational statistics. Depending on their profile, the successful candidate will work on one of the following strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer
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for automated interpretation of crystallography data for optimal ligand placement. Build and curate training datasets linking electron density maps and structural models. Design and evaluate AI models for 3D
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) ] and make use of those methods for quantum simulations [arXiv:2509.03514 (2025) ]. We have a range of interesting research avenues ahead of us, such as exploring 3D spin-systems, dynamics of spin
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to apply tensiomyography and ultrasound to evaluate skeletal muscle structure and function, able to analyze MRI images of skeletal muscles ○ Image analysis: quantify muscle architecture and fat fraction