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structures and corresponding images) needed for training and validating deep learning (DL) models. Work closely with members of the ICMN nanostructures group or external collaborators. Communicate research
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conducting fieldwork and keeping track of grant funding allocated to students or other RPDE staff. Assisting with financial management and planning, such as doing a deep-dive into the expenses or assessing
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environment to study these topics given its expertise in Machine and Deep Learning, Computer Vision, Signal Processing, and Multimedia. Also, its declared vision to work especially in presence of imperfect data
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social
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governance for climate action. 4. Guide and monitor the evolution and implementation of national platforms, extract lessons learned, and develop products to share with other cities and contexts. 5. Expand
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solutions that enhance ecological monitoring, improve resilience planning, and promote sustainable resource management. Development of a Detection Transformer through Attentive Deep Learning and Explainable
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PhD thesis Edge Intelligence for 6G Networks. The PhD project will deep dive into Edge Intelligence for next-generation (6G) communication systems. The project focuses on integrating Artificial
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appointed as lecturers to teach online courses exclusively. For more information, please visit https://www.bu.edu/eng/academics/departments-and-divisions/electrical-and-computer-engineering/current-openings
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learning architectures, addressing both Parameter-Efficient Fine-Tuning (PEFT) regimes and full end-to-end fine-tuning workflows. Where to apply Website https://www.unimore.it/ Requirements Additional