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algorithms as well as deep learning workflows on GPU servers (use of Git, Docker, and PyTorch) Design, implementation, and evaluation of spatial proteomics and multiplex analyses for characterizing the tumor
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are offering two distinct projects for this 10-week internship period. Both projects focus on the Tergite software stack, which enables the execution of complex algorithms on our 25-qubit processor
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas sensor data under varying environmental conditions. Design computer vision and human
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, particularly the strategy-as-practice and process-based research traditions, while engaging closely with AI governance and algorithmic organising. It examines how generative AI is transforming core managerial
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segmentation algorithms to segment industrial wrapped objects with limited data Develop algorithms to identify the most reliable segmented objects. Develop algorithms to determine the best grasp pose based
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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(scRNA-seq) data, and structural data from cnidarians, and we will develop new algorithms to analyze the evolutionary history of muscle components. You will study the evolution of muscle components during
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of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.]; data management and analysis solutions that assist in storage
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& Responsibilities: Assists research studies with implementation of: existing algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical