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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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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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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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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
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high-level object-oriented programming and scripting languages, such as Python and/or C++ Experience developing embedded systems for consumer and aerospace industries. Understanding of SQL database
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forecasting. Proficiency with statistical computer languages such as Python or R. Proficiency with relational database systems (SQL) and object-based data stores. Ability to define and solve logical problems
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statistical analysis software (R, Python, SPSS, or similar) preferred Experience with data modelling or database design preferred Position Type Temporary Additional Information Northeastern University considers
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knowledge of at least one major cloud platform (AWS, GCP, or Azure) Strong programming skills in Python and infrastructure-as-code tools Proficient with containerization (Docker) and orchestration (Kubernetes