Student Research Assistant - Autonomous Imaging

• Implement Vision Models: Adapt Deep Vision Models (e.g., Vision Transformers) to identify mineral features.
• Develop Autonomous Framework: Build a "Smart" scanning framework for autonomous microscope operation.
• Create Active Feedback: Implement logic to trigger high-resolution XRF and XANES scans based on real-time data.
• Validate Performance: Test the autonomous method on rare earth mineral samples to ensure efficient characterization.

• Must be a college or graduate student enrolled in computer science related or STEM field.
• You need strong skills in deep learning and programming with Python, and computer vision related technique
• You communicate effectively, both verbally and in writing.

• Demonstrated track record in computer vision or deep learning through open-source project or GitHub.
• Experience X-ray microscopy data analysis.
• Knowledge of autonomous experimentation or control systems.
• Ability to work effectively in a collaborative team to tackle challenging problems, such as automating complex scientific experiments

• Temporary/Part-time schedule of 16 hours per week.
• This position is not eligible for visa sponsorship

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