20 parallel-processing-bioinformatics positions at Lawrence Berkeley National Laboratory
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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methodology Assist with code optimization and integration into Department of Energy (DOE's) applications running on the exascale computer systems with GPU accelerators We are looking for: PhD or equivalent
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. Correlate fluorescence, label-free, mass spectroscopy, and microscopy data form a microarray platform to develop a parallel readout of protein function. Correlate and curate data from various instruments and
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distributed-memory parallel applications. Experience with containers (Docker, Podman, Shifter or similar) and modern software practices such as Git, unit testing, CI/CD, and collaborative development
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vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence
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, and manufacturing processes will focus on creating Work Instructions and Test Plans. Students with a CAD and design focus will work on 3D modeling, design, and creating manufacturing drawings. Training
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of world-class science. You will perform varied tasks essential day-to-day operation of the plant facilities systems, complete preventive maintenance, make small and complex equipment repairs, monitor and
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architectures for science Developing and advancing extreme-scale scientific data management, analysis, and visualization Developing and advancing next-generation machine learning, AI, and data science approaches
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worldwide. In this role, developers create and operate robust, mission-critical solutions that collect, process, store, and present network measurements and event data using open-source and cloud-native
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-tuning and/or Retrieval-Augmented Generation (RAG) methods to augment LLMs with dedicated knowledge in transportation and electric grid domains. This involves designing methods to process input data and