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PyTorch, including model training, fine-tuning, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi
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computing environments (e.g., GPU ‑ enabled systems, shared compute clusters). Working knowledge of database systems, including: Relational databases (e.g., PostgreSQL / SQL) Exposure to graph
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engineering, and operational AI systems. Candidates who can additionally bridge these disciplines into information security or cloud computing contexts are especially welcome. Qualified candidates must be
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simulations, sampling techniques, machine learning, or quantum computing; experience in two or more areas is a strong plus Strong oral and written communication skills with a willingness to contribute to a
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postdoc will contribute to and help lead projects that may involve concepts and priorities such as knowledge-graph-driven data integration, AI-powered literature review, agentic database search
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’s will assist with growing our Co-Op program and engage with Northeastern University Faculty to offer services when appropriate. ISSO Track: This position will support classified computing
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, preferably in an environment that deployed 3+ modules. Demonstrated success in vendor and stakeholder management. In-depth knowledge of enterprise application platforms, cloud computing, immersion
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computing, and develop machine learning algorithms. With a passion for high-performance technology, large-scale machine learning, and AI-type algorithms, students become intuitive problem solvers
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-level object-oriented programming and scripting languages, such as Python, C++, Java Experience with high-performance computing environments. Understanding and experience with Python frameworks, such
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approaches software development from the analytical and methodological perspective of an engineer. Students build advanced design and engineering skills, enhance their knowledge in cloud computing, and