Master's student position or internship Machine learning / Deep learning ai-jobs.net

Many application domains increasingly require AD, when anomalies carry critical and actionable information. We shall address the problem of detecting and predicting general anomalies in high-dimension KPI performance metrics, i.e., high dimension and dynamic range multivariate non-stationary time series collected from large Cloud / IT environments. Using Keras / TF etc., we will build an ML-based AD framework for transfer, attention and meta-learning that must remain robust also with reduced/missing and noisy training data. Besides feature engineering -- e.g., selection, reduction, compression techniques -- explainability will also be necessary for the model prototype. The research is to be performed at IBM Research – Zurich Lab, Switzerland.