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: Education: Bachelor in Biosciences, or Engineering degree in Computer or Data Sciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: previous experience working with
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, using fast cameras, radiation detectors, and deep-learning architectures capable of operating within milliseconds. It will also include collaboration with medical physicists and clinicians to integrate
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https://www.academictransfer.com/en/jobs/357205/2x-phd-positions-in-the-mathema… Requirements Specific Requirements You have, or will shortly, acquire a Master's degree in either Mathematics
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the dispersion of these macroplastic items in these flow fields; comparing the results of the simulations to results from an experimental campaign of floating trackers; collaborating with a postdoc and two PhD
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invites applications for a full-time, Non-Tenure Teaching Track, Assistant Professor position with a specialization in Generative AI, Large Language Models (LLMs), and Deep Learning. We seek a dynamic
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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scholarship + CEITEC PhD School scholarship. Requirements on candidates: Motivated smart people that have the “drive” to work independently, but also willing to learn from other people in the lab and
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Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines Minimum Number of References Required Maximum
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, mathematical logic or statistical learning theory. For PhD position 2, we appreciate prior experience in implementing deep learning models for graphs and networks. Our offer As a PhD candidate at UT, you will be
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to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more information, please visit