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open-source research software packages; Publish research results in high-quality journals and competitive conference venues. Due to the nature of the work, the selected applicant will be required to work
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implementation of constitutive models within commercial and/or open-source finite element software is required. Preferred Qualifications: Demonstrated expertise in multi-physics FE simulations is preferred
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-changing needs Preferred Qualifications: Experience in radiological risk assessment Experience in biokinetic model development Experience with Monte Carlo radiation transport software and applications
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an international team. -Ability to multi-task and work cooperatively with others. -Ability to utilize a computer and applicable software to create databases, perform statistical analyses, present data and perform
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AI or machine learning applications. Formal training or professional experience in audio engineering, recording arts, or signal processing. Experience with acoustic software platforms (e.g., Pro Tools
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relevant technical software, such as Cadence, SPICE, Verilog, etc. are needed; • Background knowledge in neural network algorithms preferred, but not required • Collaborative skills, student mentorship
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experience using statistical software (e.g., R and Python) and AI tools (e.g., Claude Code) are a key requirement for the position. Successful candidates should show potential to excel in tasks related to meta
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structure data PREFERRED QUALIFICATIONS Experience with R software packages SALARY: $4,166.67 - $4,791.67 Monthly ($50,000 - $57,500 Annually Approximately) NOTE: This a grant-funded position. Continued
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computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data analytics, including correlation analysis and machine learning techniques. Preferred
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-mining/NLP pipelines). Experience developing research software that supports end users, including building web-based tools/platform features, APIs, dashboards, and deployable prototypes (level of depth can