Multi-modal Sensing AI Research Intern
Core
Develop state-of-the-art multi-modal models for active (radar, ultrasound) and passive sensing (acoustic, vibration, EEG) use-cases using classical signal processing and machine/deep learning-based approaches.
Role type
Research intern (multi-modal sensing AI)
Builds
Multi-modal representation learning solutions and modality adaptation models
Domain
AI research, signal processing, sensor data
Deliverable
research
Required skills
PyTorch, HuggingFace transformers, Hydra, machine learning algorithms, deep learning principles
Preferred skills
Raw sensor data processing, digital signal processing, multimodal representation learning, HPC platforms (Slurm, IBM LSF)
Technologies
PyTorch, Lightning, HuggingFace, Hydra, Slurm, IBM LSF
Responsibilities
Develop multi-modal models for sensing use-cases, research solutions for representation learning and modality adaptation, evaluate models on downstream applications, summarize findings in papers or patents
Seniority
Intern
