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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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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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working with ML/AI (TensorFlow/Pytorch) and ETL pipelines. ● Proficiency in Python and R. Experienced with Unix and remote computing clusters. ● Having experience in wrangling large datasets, building
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-oriented programming and scripting languages, such as Python, C++, C#, Java, JavaScript, etc. Interest in Computer Vision, ML, and AI concepts. Ability to lead a small team of engineers and share knowledge
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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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or Python. Lastly, candidates should have experience performing human subjects experiments. Application Material: Curriculum Vitae with pointers to your research/expertise-related online profiles (e.g
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NIST SP 800-53rev5 and IETF RFCs on security protocols. ● Proficiency in full stack development (e.g., front-end: React, Angular, Vue.js; Back-End: Node.js, Python, Go, or Java). ● Familiarity with VLANs
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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