Multimodal AI Algorithm Expert-EMG / Interaction Perception, Pico

What you'll do

• Develop deep-learning models at the intersection of sEMG, computer vision, and IMU technologies.
• Build sEMG acquisition pipelines and perform signal-quality optimization, denoising, and feature extraction.
• Develop multimodal spatiotemporal fusion methods and improve algorithm performance and generalization amid sensor noise.

What they ask for

• Master’s degree or above in a relevant field.
• Substantial experience training and deploying deep models; experience fine-tuning end-to-end speech recognition frameworks and familiarity with 2D/3D computer-vision perception algorithms.
• Familiarity with sEMG acquisition and processing, including denoising and feature extraction.
• Experience with digital signal processing techniques such as filtering, Fourier transforms, correlation analysis, and modulation.

Nice to have

• Experience analyzing and modeling high-dimensional time-series data, such as speech, neural, physiological, video, or sensor data.
• Publications at accredited conferences or participation in listed competitions and challenges.

Tools

sEMG, computer vision, IMU, Transformer, LSTM, Spatiotemporal Convolutional Networks, Conformer, RNN-T

AI focus

Research and develop deep-learning models for multimodal interaction perception, including sEMG signal processing and fusion with computer-vision and IMU data.