We are looking for a motivated Machine Learning Intern to work on an exciting project involving satellite telemetry data. The goal of this internship is to develop a proof of concept tool for detecting and predicting anomalies and extracting insights from time-series satellite telemetry data using modern machine learning techniques.

ISISPACE develops and maintains its own Mission Control Centre to operate satellites. We have a significant satellite telemetry data set for previous and active missions. We are continuously working on improving our capabilities in telemetry analysis. This assignment will contribute to that goal.

You will work on real-world engineering data and contribute to a project that explores how data-driven methods can improve system monitoring, reliability, and operational awareness in satellite systems. You will have the opportunity to gain hands-on experience in applied machine learning, time-series analysis, and data engineering within a practical domain.

If this sounds exciting to you, we are looking forward to receiving your application!

Specific tasks and responsibilities include

· Explore and analyze satellite telemetry datasets.

· Clean, preprocess, and structure time-series data.

· Design and implement feature engineering pipelines.

· Develop and test machine learning models for anomaly detection and/or forecasting.

· Evaluate model performance and analyze results.

· Visualize telemetry data and model outputs.

· Document methodology, findings, and recommendations.

· Summarize findings and recommendations.

Requirements

· Currently pursuing a degree in computer science, data science, aerospace engineering, or a related field.

· Experience with Python and machine learning.

· Pro-active, clear, and open communication in English.

· Familiarity with Git version control.

· Comfortable working independently and in a small team.

Nice to haves

· Experience with Scikit-learn, PyTorch, or TensorFlow.

· Experience with Time-series modeling (ARIMA, LSTM, etc.).

· Understanding of Satellite systems or telemetry data.

· Interest in space systems or aerospace applications.