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packages and tools (e.g., Numpy, Pytorch, Tensorflow, ART). You have knowledge or familiarity with reverse engineering tools (e.g. NSA Ghidra, IDA Pro) You have experience with Python, C/C++, or low-level
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domains) Experience with RF signal analysis and wireless communication systems Experience with SDR platforms (e.g., USRP) and IQ data processing Experience with MATLAB and Python Excellent written and oral
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programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions
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Qualifications Education: ABD status by start date. PhD by start date in a field relevant to the research being conducted. PhD after one year of employment. Technical Skills or Knowledge: Proficiency in Python
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experience with new IBR models (e.g., WECC REGFMA1, REGFMB1, vendor-provided models) is a plus. Experience with software development in Python, C++, or other programming languages. Hands-on experience
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong
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learning models, and willingness to learn about new methods, is a plus. · Strong programming skills in Python, and Linux Shell; experience in developing methods as open source repositories at e.g. GitHub is
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. Programming experience in Python. Excellent communication skills and fluency in English. Collaborative personality with attention for detail. Bonus but not requiredExperience with training and validating
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Programming experience in Python Excellent communication skills and fluency in English Collaborative personality with attention for detail Bonus but not required Experience in imaging or spatial omics data
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. Preferred Qualifications Knowledge of aging-in-place, accessibility, or universal design. Experience with AR/VR tools, programming/coding (Python, R, Unity, or JavaScript), or community-engaged research