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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
environment Access to state-of-the-art tools and computational infrastructure, including CPU/GPU clusters Opportunity to contribute to cutting-edge research in plant evolution and genomics Support
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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data
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), or reinforcement learning (RL) post-training. Experience with multi-GPU training and a strong working knowledge of reinforcement learning are also required. Familiarity with standard software development tools
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC-Chapel Hill, Duke University, and North Carolina State University all
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
, including the 17,000-core Longleaf cluster optimized for I/O intensive workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC-Chapel Hill, Duke University, and North Carolina State University all
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
, including the 17,000-core Longleaf cluster optimized for I/O intensive workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC
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signal processing (GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral
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. Preferred Qualifications Experience with: C/C++, Python, MATLAB, ROS 1 and 2, OpenCV, Unity, GPU programming, linear and nonlinear control theory, supervised, unsupervised and reinforcement learning, Torch
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computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI environments and tools. Prior experience