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Field
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generation to build tools that will shape the future of home-based rehabilitation monitoring. You bring: A PhD in Biomechanical Engineering, Biomedical Engineering, Computer Vision, Robotics, or a related
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also provide shared office space, and a laptop computer. Further information can be found at https://piirs.princeton.edu/funding-fellowships/piirs-postdoctoral-fellows . This position is subject to the
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Base Salary $117,936 - $125,896 + 17% superannuation About the opportunity The Centre for IoT and Telecommunications (CIoTT) in the School of Electrical and Computer Engineering is seeking a Postdoctoral
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distribution. Both projects will develop the Fontan emulator to be patient-specific, MRI compatible, computer controlled, and quantitatively evaluated using advanced bench-top, CFD/FSI simulation, and MRI-based
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of agentic behavior and publishing high-impact research Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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skills and experience; strong computer skills including Excel, statistical and/or graphical software (ex. Adobe Illustrator, ImageJ, Powerpoint); excellent organizational and communication skills; ability
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
-10346 Requirements Skills/Qualifications PhD in Computer Science, Machine Learning, Signal Processing, or a closely related field, completed or nearly completed at the start date. Strong background in
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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specialist knowledge in the discipline to work within established research programmes. You will also have experience writing computer code in Stata and/or R for data analysis and visualisation and have
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spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s disease from a disease without cures into a predictable