- study the state of the art on machine learning algorithms for distributed data streams; - study technologies for the management distributed data streams in networks (e.g. Apache Kafka, ZeroML, RabbitMQ); - select and apply studied algorithms in a diverse set of problems (e.g. anomaly detection, classification, regression, recommendation); - implement algorithms in a distributed machine learning platform, as well data connectors and access APIs; - evaluate the system in the proposed problems; - develop an MSc dissertation; - draft a scientific paper proposal.
Degree in Computer Science, Informatics, software Engineering or similar area
Minimum profile required
- final degree grade of 15 (in a 0 to 20 scale);- knowledge of machine learning, proven by university academic curriculum or participation in applied machine learning projects.
- experience with distributed machine learning algorithms and/or data streams; - experience in research projects in the area of artificial intelligence.
Since 19 May 2021 to 01 Jun 2021
Cluster / Centre
Computer Science / Artificial Intelligence and Decision Support