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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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building a positive environment to grow and groom future business leaders. And we are looking to add to our BIZ family! To learn more about the NUS Business School, please visit https://bschool.nus.edu.sg
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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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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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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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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
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[map ] Subject Areas: Mathematics, AI-based drug design and discovery, Bioinformatics/Protein Engineering/Single-cell Omics Data, Mathematical AI/Machine Learning/Deep Learning, and Computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 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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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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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