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We are seeking a highly motivated and innovative researcher working at the interface of modeling complex system and AI to join our team developing Large Language Models (LLM) based agentic code
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with unsupervised ML algorithms such as autoencoders, clustering Programming expertise in Python, or another scientific programming language is highly desirable Ability to model Argonne’s Core Values
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Language Models for scientific applications. ALCF is also a leader in training the next generation of scientists to utilize supercomputers to further their research. The facility is looking for a
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of and experimental expertise in catalyst-material characterization techniques. Familiarity with mathematical and computational modeling, and competence in a scientific programming language (e.g
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literature. Position Requirements A PhD in Materials Science or a related field is required. Ability to code in Python and working knowledge of large language model is required. Experience with literature data
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performance FPGAs is highly desirable Experience with FPGA programming languages (vhdl or verilog) is required Programming expertise in C, C++, Python, or another scientific programming language is highly
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on the Python programming language and contributions to open-source scientific software Good scientific productivity, as demonstrated by publications and conference presentations Effective oral and written
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applicants with a combination of engineering background and extensive knowledge and experience of Python programming language, including building application programming interfaces (APIs), integrations using