Bosch Research Pittsburgh would like to invite an enthusiastic and knowledgeable machine learning research intern for investigations at the intersection of natural language processing, multimodal representation learning, and sequential decision-making. We wish to develop adaptive intelligent systems, capable of reasoning over various sensor data streams and heterogeneous data sources (e.g., video feeds, textual meta-data, knowledge graphs) in order to satisfy such downstream tasks as video content understanding, visual question-answering, building automation/control, or natural language robot navigation. We expect the intern to implement and evaluate various methods, inspired by both your own insights and by contemporary academic literature. Viable methods include end-to-end neural systems and hierarchical AI methods; regardless of the chosen method(s), the intern must understand the relevant challenges of dataalignment, practical implementation, model generalizability, overall system robustness, and performance characterization. Together with our faculty collaborators in the School of Computer Science and College of Engineering at Carnegie Mellon University (CMU), we have made several key developments that we expect the prospective intern to leverage and extend. Finally, the prospective intern will work with teammates to publish a research paper in a top-tier AI venue. Tasks
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
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