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Field
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programming, algorithm development and deep learning model implementation, and practical experience in drone and boat-based surveys are preferred. Background Investigation Statement: Prior to hiring, the final
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Develop instrumentation and fixtures for the automation. Capabilities in advanced finite element or machine learning tools for process optimisation Disseminate the research outcomes into Journal
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for MND which could be translated into the clinic. The idea is to use cutting edge machine learning to create clinically actionable predictions such as the time from diagnosis to requirement for a
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machine learning. The specific goal is to extend new and existing visualization environments to support efficient and precise annotation of histopathology images using a combination of expert human review
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biology, engineering, biophysics, computer science) and experience in 3D imaging of brain tissue, image segmentation, and handling large datasets. You are comfortable with machine learning and image
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references is required. To learn more about AI at Princeton, please visit https://ai.princeton.edu. Princeton University is committed to fostering a diverse and inclusive academic community. To maximize
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, the participant will learn HPC computing technologies and techniques in genomic epidemiology and machine learning to quantify drivers of IAV evolution in swine using data generated from IAV surveillance in human
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Pose EstimationStrong background in computer vision and machine learning applied to pose estimation and visual servoing; Experience with OpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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at https://puwebp.princeton.edu/AcadHire/position/40281 and submit a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more