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programming skills (for example MATLAB and/or Python) are highly preferred but not required. A two-year commitment is required. ADDITIONAL JOB DETAILS: The Translational Research in Affective Disorders
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least five years of experience in software development, with at least one year in a senior developer role. Experience with a range of programming languages, which could include Python, VBScript, HTML, SQL
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. Support backend engineering initiatives based on scalable Python microservices, contributing to architectural reviews, code quality improvements, and production-grade deployment practices. Design and
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such as Python, C/C++, or Java. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and geospatial libraries (e.g., GDAL, GeoPandas). Experience managing or supervising
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/ ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation
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mathematical analysis, numerical exercises using Python, and participatory demonstrations of mechanical systems. Number of Positions: 1 Estimated course enrolment: 92 students Estimated TA support: TBA hours
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. More information about Dr. Card and the lab’s research can be found by visiting https://www.hhmi.org/scientists/gwyneth-card About the Mechanical Engineer role: You will be a general-purpose engineer
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languages (e.g., R, SAS, Python). Working Conditions Office-based. Application Documents Resume (required) When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled
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communication skills in written and spoken English. Proficiency in programming with high-level languages like Python. The following will strengthen your application: Familiarity with open quantum systems
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
), with evidence in open-source code or deployed tools. - Solid programming and ML/NLP engineering skills in Python or ideally modern deep-learning stacks (e.g., PyTorch/JAX, HuggingFace/Transformers