9 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" positions at Lawrence Berkeley National Laboratory
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-structured, accessible, and optimized for use by domain scientists and downstream AI applications. This position will analyze complex business and data management challenges and will design automated, cost
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to enhance energy efficiency and building operability. Develop and implement detailed control sequences and engineering solutions across multiple concurrent projects. Prepare analyses, designs, construction
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the Laboratory's tripartite governance structure (DOE-UCNL-LBNL) and advocate for continued infrastructure modernization and operational investment. Promote "One Lab" alignment between Science and Operations
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library construction and sequencing procedures. Use, design, and develop new tools to analyze assembled sequences of various research projects. Quantitatively evaluate assembly results and use them
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documents into appropriate structures for efficient training, establishing evaluation metrics to validate model performance, and improving the fine-tuning process with additional reinforcement learning steps
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in interpreting X-ray and TEM data for material structure and composition analysis. Strong communication skills, collaborative mindset, and the ability to work effectively across multidisciplinary
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workflows. Experience in design, construction and programming of robotic laboratory equipment and/or automated microscopes. Experience in modular, multi-threaded GUI development for scientific applications
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. Familiarity with object storage systems such as MinIO or AWS S3 and understanding of data lifecycle management in distributed storage. Familiarity with Apache Spark (PySpark, SparkSQL, or Structured Streaming
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cabling and piping layouts, 3D printing, opto-mechanical systems, mechatronics, vacuum systems, structural supports, or design for manufacturability/assembly. Ability to assist in developing work