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Ph.D. with demonstrated R&D experience. Development experience with bash scripting and Python, and/or embedded development (C/C++/etc). Knowledge on cellular systems, 3GPP, open RAN. Knowledge of Linux
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statistical modeling, machine learning, data analysis, and reporting Proficiency in Python or R Ability to plan, execute and control a project, establishing realistic estimates and reporting timelines Advanced
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personal style willing to receive assistance and coaching when needed from the faculty lead. Prior experience in a diverse higher education institution preferred. Knowledge of Python and/or R programming
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personal style willing to receive assistance and coaching when needed from the faculty lead. Prior experience in a diverse higher education institution preferred. Knowledge of Python and/or R programming
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Ph.D. in science (chemistry, physics, biology, etc.) or engineering required 7+ years of experience in computational physics or related area Proven experience coding in C/C++, Fortran, and/or Python
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skills with proficiency in Python, TensorFlow/PyTorch, and experience with containerized deployments and MLOps practices. Data Pipeline Engineering: Extensive experience with end-to-end data pipelines
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ML systems into production environments, with a focus on performance, robustness, and scalability. Domain expertise in NLP, computer vision, or speech processing. Proficient in Python for software and
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workloads including embedding generation, LLM inference, and cognitive search. Develop Snowpark Python transformations, UDFs, and machine-learning features. Implement vectorized storage, model-serving
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cognitive search. Develop Snowpark Python transformations, UDFs, and machine-learning features. Implement vectorized storage, model-serving patterns, and AI-ready data transformations. Support RAG/semantic
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limited sample proteomics is highly desirable. Knowledge of R or Python coding would be desirable but not necessary. Applicants must include the following with their application: 1. Resume/CV 2. Cover