Intern

Overview

An Advanced Research internship in Artificial Intelligence at GE Vernova's research organization, focused on time series analysis, machine vision and deep learning applications for the energy sector.

What you'll do

• Assist in designing and developing research experiments to address key challenges in time series analysis, machine vision, and deep learning applications.
• Develop novel AI/ML algorithms and implement them in Python, PyTorch, TensorFlow, or similar environments.
• Build and evaluate machine learning and deep learning models for the analysis of time series data and visual data; conduct experiments to validate algorithm performance across various datasets and scenarios.
• Analyze experimental results to validate theoretical assumptions, assess model accuracy, and derive actionable insights for further refinement.
• Conduct comprehensive literature reviews to stay abreast of state-of-the-art techniques in time series forecasting, computer vision, and deep learning architectures.
• Document research methodologies, experimental setup, results, and findings in technical reports, papers, and presentations for both internal and external dissemination.

What you'll need

• Currently enrolled in a Master's or Ph.D. program in Computer Science, Electrical/Electronics Engineering, Applied Mathematics, Data Science, or a related field, with a focus on AI, Machine Learning, or Data Analytics.
• Experience developing in Python and familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or Keras.
• Proficiency in building and evaluating statistical, machine learning, and deep learning models for time series and/or image data.
• Experience with data processing, feature engineering, and data visualization tools and libraries (e.g., NumPy, pandas, matplotlib, OpenCV).
• Excellent analytical and problem-solving skills, with the ability to critically evaluate research findings and propose innovative solutions.
• Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment.

Details

• Location: Bengaluru.
• Relocation assistance provided.