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Field
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in data science, computer science, computational biology, or a related field Solid programming and data science skills, including familiarity with Linux, Python programming, version control, continuous
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programme of computer science, mathematics, physics, electrical engineering, computational linguistics, or similar with good grades PyTorch skills: experience in training machine learning models with one
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, advancing bioinformatics-driven research, facilitated by exceptional computational infrastructure including a centrally administered high-performance CPU and GPU cluster and network storage. This includes
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computing frameworks (e.g., MPI, NCCL) and model parallelism techniques. Proficiency in C++/CUDA programming for GPU acceleration. Experience in optimizing deep learning models for inference (e.g., using
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research. Strong technical expertise in large scale data analysis, statistical and simulation tools, machine learning, AI and GPU programming. Experience with one more of these scientific collaborations
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partner with ORNL research organizations to enable research excellence and delivery. We work with other clustered computing and HPC groups to help research programs identify the best solutions
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performance. The Project/Program Manager (Systems Engineer) focuses on the deployment, configuration, monitoring, and maintenance of GPU-enabled servers, virtualized environments, and hybrid infrastructure
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support to meet individual user and program needs. The individual will independently collaborate with the IT partners on Campus and School of Medicine to fulfill the technical mission of the NCIBT
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engineering, and IT training and technical support to meet individual user and program needs. The individual will independently collaborate with the IT partners on Campus and School of Medicine to fulfill
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Description Primary Duties & Responsibilities: Lead the optimization of large-scale LLMs and deep learning architectures for biomedical research. Design and deploy high-performance AI systems using GPUs and