Found Description
Hybrid - 2 days in Office 3 days WFH
Summary:
Build, train, and deploy large-scale, self-supervised "foundation" models that learn rich representations of time series, sequential sensor data in addition to textual and vision data, to be fine-tuned for tasks such as anomaly/event detection, predictive maintenance, forecasting, classification, or multi-modal sensor fusion for industrial and scientific applications.
Data/Signal Processing
• Time Series & Sequential Data: processing, augmentation, feature engineering for financial, industrial, IoT, medical, or other sensor streams (univariate/multivariate time series).
• Sensor Data Analysis: expertise with diverse sensor modalities (e.g., accelerometers, temperature, vibration, audio, images), sampling rates, synchronization, and real-world noise/artifact handling.
• Multi-Modality Learning: integrating heteroge...
Summary:
Build, train, and deploy large-scale, self-supervised "foundation" models that learn rich representations of time series, sequential sensor data in addition to textual and vision data, to be fine-tuned for tasks such as anomaly/event detection, predictive maintenance, forecasting, classification, or multi-modal sensor fusion for industrial and scientific applications.
Data/Signal Processing
• Time Series & Sequential Data: processing, augmentation, feature engineering for financial, industrial, IoT, medical, or other sensor streams (univariate/multivariate time series).
• Sensor Data Analysis: expertise with diverse sensor modalities (e.g., accelerometers, temperature, vibration, audio, images), sampling rates, synchronization, and real-world noise/artifact handling.
• Multi-Modality Learning: integrating heteroge...