Job Description/Specification:
Carnegie Mellon University is seeking a motivated Research Assistant to join an innovative research project focused on indoor context-aware systems, localization, wearable sensing, and indoor trajectory prediction. The successful candidate will contribute to research, prototyping, data collection, and analysis while working with multidisciplinary team members and external collaborators.
About the Role
The Research Assistant will support the development of multi-modal deep learning solutions and help create comprehensive datasets for indoor trajectory prediction. The role offers an opportunity to work with wearable multi-sensor technologies, sensor integration, machine learning, and real-world data collection in a research-driven environment.
Key Responsibilities
- Assist in developing context-aware indoor systems using multi-modal deep learning techniques.
- Support indoor localization and trajectory prediction research activities.
- Prototype and test wearable multi-sensor devices for indoor data collection.
- Collect, organize, annotate, and validate multi-modal datasets.
- Integrate sensors and support experimental data acquisition.
- Analyze research data and contribute to interpretation of results.
- Assist with research documentation, technical reports, and presentations.
- Collaborate with researchers, project team members, and external partners.
- Support testing, troubleshooting, and continuous improvement of research prototypes.
Minimum Requirements
- Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field.
- Strong programming skills in Python and C/C++.
- Familiarity with deep learning and machine learning frameworks, particularly PyTorch.
- Working knowledge of Linux and command-line environments.
- Experience with sensor integration, data collection, processing, and analysis.
- Strong analytical, problem-solving, and research skills.
- Ability to work effectively in a collaborative research environment.
Technical Skills
Python | C/C++ | PyTorch | Deep Learning | Machine Learning | Linux | Command Line | Sensor Integration | Multi-Modal Data | Data Collection | Data Annotation | Indoor Localization | Trajectory Prediction | Wearable Sensors | Data Analysis
What You Can Expect
Eligible Carnegie Mellon employees may have access to comprehensive medical, prescription, dental, and vision coverage, retirement savings programs, tuition benefits, paid time off, holidays, life and disability insurance, transportation benefits, fitness facilities, and additional employee support programs.