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Field
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planning and execution frameworks. Required Qualifications Minimum of a HS Diploma or GED. Strong proficiency in Python and experience with LLM APIs (e.g., OpenAI, Anthropic) or open-source frameworks (e.g
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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research and developing decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more
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mechanics and analysis Experience with the following: Structural health monitoring (SHM) Finite element modeling (e.g., ABAQUS, SAP2000, ANSYS) Machine learning / AI (Python, TensorFlow, PyTorch) Demonstrated
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one of the following programming languages: C++, PERL, Python, R, Java Experiences with high-throughput sequencing data (WGS, WES, RNA-Seq, ChIP-Seq) analysis Excellent oral and written communication
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 2 hours ago
science databases. This data analysis may be performed using various programming languages such as, SAS, R, or Python. As part of this opportunity, you will be able to engage with a multi-disciplinary
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interpret research datasets, drawing meaningful conclusions using appropriate statistical methods and scientific reasoning. Develop and optimize computational pipelines, scripts, and workflows using Python
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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to spatter landing sites Analyzing data from experiments using Python Train and validate machine learning model for processing data Writing/submitting manuscript of work to academic journals for publication
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include MATLAB, Labview, Python and/or C++. Requirements: PhD Duke is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability