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our publications here . Our team is at the forefront of bringing autologous cell replacement therapies with CRISPR-edited muscle stem cells towards the clinic (https://www.mdc-berlin.de/news/news/deep
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transportation systems and autonomous driving. • Strong understanding of generative AI, deep learning, and multimodal machine learning, with hands-on experience. • Excellent programming skills and proficiency with
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simultaneous and quantitative measurement of large cytokine panels, combining deep multiplexing with reduced variability and cost. In this project, you will help build a next-generation, antibody-free
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) and will teach one course per semester in the Department of Anthropology’s terminal Master’s (MAO) Program and work with the Director of the MAO Program. Successful candidates must have their PhD by
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year (renewable) Appointment Start Date: June 1, 2026 (flexible start date) Group or Departmental Website: https://butzindozier.com (link is external) How to Submit Application Materials: Please email
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relevant to the content of the ROSETTA project (https://rosetta-project.eu/ ). Applications featuring a PhD in a behavioral science–related field (e.g., marketing, consumer behavior, psychology
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection
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the metropolitan area of Marrakech. The School of Computer Science at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco, is seeking a postdoctoral candidate in the area of federated learning and wireless
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of photovoltaic solar potential Duration: 3 months Maximum Duration Including Renewals: 3 months Monthly Maintenance Allowance: €1,851.00 Where to apply Website https://fenix.tecnico.ulisboa.pt/fenixedu-admissions
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implement state-of-the-art data science principles into dental practice. While our primary focus is on the use of deep learning in (dental) imaging, our work expands into any type of data (e.g. tabular data