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: Experience with time-series analysis, predictive modeling, and anomaly detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms
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of transformer architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time-series data, anomaly detection, or predictive maintenance is a strong plus. Familiarity with industrial
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discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease progression modeling. Explainability and interpretability of AI models to support clinical decision
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related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools