Data Scientist – AI

1 week ago

Canada, CA CrowdPlat Part time

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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