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Description The School of Social Work is seeking a graduate student with experience in spatial data analysis using Python to support faculty research projects. The ideal candidate will have experience working
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Requirements: Minimum Bachelor’s degree in computer science/ engineering or related fields. Proficiency in programming languages such as Java, Python, Go, C/C++ or other backend development languages is required
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analysis through coursework, research projects or employment. Familiarity with cancer genomics and statistical methods Good written and oral communication skills Proficiency in in R or Python for data
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or programming knowledge such as Python, Bash, or PowerShell is advantageous. Experience with servers, GPU systems, workstations, virtualization, cloud platforms, scientific computing, or AI/ML research
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methods Proficiency in Python and/or C++ for robotics and ML systems Experience with modern deep learning frameworks (e.g., PyTorch) Ability to design experiments, analyze failures, and iterate quickly in
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ideas to understand how design shapes behaviour and experience. Students are introduced to key tools and platforms such as Arduino and sensors, TouchDesigner, and introductory Python programming
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venues (e.g., CVPR) and leading peer-reviewed remote sensing journals (e.g., IEEE TGRS). The candidate should have strong programming skills in Python and MATLAB, together with practical experience in deep
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enhance graphics functionality across BSI software products. Assist with developing internal validation and testing tools using Python scripting and leveraging Azure DevOps for project management
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Knowledge of ERP/financial systems (e.g., Workday, Adaptive Planning, Oracle, or similar) Working knowledge of Python or R for data automation and analysis Experience with cloud data platforms (e.g
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and affects control accuracy in Si/SiGe spin-qubit systems Develop compact Python-based models of these electronics for integration into quantum-mechanical simulations Design and evaluate cryogenic