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Field
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, deploy, and maintain distributed systems and cloud infrastructure which includes contributing to cloud architecture definition and performing design and implementation within established architecture
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in neurons and in vivo . Our group makes use of metabolic biosensors and behavior in C. elegans to uncover how neuronal energy states are distributed across cells and tissues, and how this
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Engineering at Scale : Profile, model, and optimize distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross
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, benchmarking, and validation methods • Microservice-based, cloud-native, edge, and distributed software systems • Interoperability frameworks, data integration, and cross-system communication • Digital twin
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scientific data to advance research efforts across scientific systems. Develop and apply federated learning on distributed and heterogenous datasets. Develop more efficient and resilient DP techniques that
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observations should occur, and which asset can capture the event first. This requires distributed onboard AI capabilities for task allocation, resource management, and real-time constellation coordination
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Learning and Computer Science, MBZUAI. Dr. Ho specializes in distributed machine learning and systems architecture. His expertise drives the design of robust, parallelized systems required to scale
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areas include: Parallel and distributed graph and or ML algorithms — shortest paths, connectivity, clustering, or graph traversal on GPU clusters and distributed-memory systems. Sparse direct and
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for OPF and related grid simulation tasks. Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on
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). We are looking for a person with: A PhD in computer science or a related field, with a software systems profile: distributed systems, cloud or edge computing, simulation, digital twins, model-based