Clean and preprocess GPR data to ensure high-quality input for machine learning models.
Handle missing or inconsistent data effectively.
Feature Engineering:
Work closely with the Senior Engineer to identify relevant features from GPR data for model development.
Contribute to the development of new features based on domain knowledge.
Model Development:
Assist in building and fine-tuning machine learning models for underground terrain prediction.
Implement algorithms under the guidance of the Senior Engineer.
Collaborate with the team to experiment with different model architectures.
Evaluation and Validation:
Conduct model evaluation and validation to ensure robust performance.
Implement metrics to measure the accuracy and reliability of the models.
Documentation:
Document code, models, and experiments effectively for knowledge sharing and future reference.
Collaborate with the team to maintain clear and comprehensive documentation.
Collaboration:
Work closely with cross-functional teams, including domain experts and software engineers, to integrate machine learning models into practical solutions.
Participate in team discussions and contribute innovative ideas to enhance model performance.
Learning and Development:
Stay updated on the latest advancements in machine learning, deep learning, and GPR technologies.
Actively engage in continuous learning and skill development.
Requirements:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
Solid understanding of machine learning concepts and algorithms.
Proficiency in programming languages such as Python.
Familiarity with deep learning frameworks including TensorFlow and PyTorch.
Strong problem-solving skills and attention to detail.
Excellent communication and collaboration skills.
Experience - 1+ years (in addition to the academic projects)
Basic knowledge of signal processing and GPR technology is a plus.
