Data Scientist – AI
1 week ago
Key Responsibilities:
- Algorithm Development and Optimization:
- Develop, train, and deploy Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) to enhance the resolution and accuracy of lunar DTMs.
- Use Python-based libraries like TensorFlow and Keras to design Super-Resolution CNNs (SRCNN) and GANs (SRGAN) for high-resolution terrain mapping.
- Data Processing and Model Training:
- Preprocess digital elevation models (DEMs) and lunar orbiter images, applying normalization, alignment, and advanced image registration techniques.
- Train the SRCNN and SRGAN models on high-quality lunar datasets, including data from NASA’s Lunar Reconnaissance Orbiter Camera (LROC) and ShadowCam instruments.
- Integration with Traditional Image Processing Techniques:
- Combine photogrammetry and photoclinometry outputs with AI models to achieve pixel-level precision in terrain mapping.
- Utilize the Ames Stereo Pipeline (ASP) to process high-resolution images into 3D terrain models for accurate lunar surface modeling.
- Performance Monitoring and Model Validation:
- Monitor model performance using metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) to ensure high accuracy.
- Perform cross-validation to ensure model generalization across different lunar regions.
- Documentation and Collaboration:
- Create and maintain detailed documentation of algorithms, models, and data preprocessing methods.
- Collaborate closely with data scientists, planetary scientists, and NASA’s lunar mapping experts to align model outputs with mission requirements.
Requirements:
- Technical Skills:
- Proficiency in Python and experience with machine learning frameworks, specifically TensorFlow and Keras.
- Familiarity with image processing libraries (e.g., OpenCV) and 3D modeling tools.
- Knowledge of Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), and other deep learning techniques.
- Experience:
- 3+ years of experience in algorithm development, particularly for image processing or terrain modeling.
- Prior experience with photogrammetry, photoclinometry, or remote sensing data is highly desirable.
- Background in geospatial data, planetary science, or a related field is a plus.
- Soft Skills:
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication and documentation skills.
- Ability to work collaboratively within a multi-disciplinary team and independently manage technical tasks.
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