AI Research Intern – Hybrid AI for Autonomous Driving
Job Description
Bosch Research Pittsburgh would like to invite an enthusiastic research intern for investigations at the intersection of knowledge representation and machine learning. The intern will help to develop novel algorithms and methods relevant for autonomous driving. More specifically, they will develop Knowledge Graph Embeddings (KGE) from multimodal data of driving scenes and use these embeddings for various scene understanding tasks, such as object prediction, scene similarity, scene classification, etc.
We expect the intern to perform implementation and evaluation of various methods, inspired by their own insights, team discussion, and contemporary academic literature. Viable methods may comprise: semantic web technologies, with a focus on knowledge graphs and knowledge graph embeddings; machine learning, including traditional approaches and more recent deep neural methods. Regardless of the method(s), the intern must understand the relevant challenges of developing a neuro-symbolic AI architecture.
At Bosch Research we have made several key developments that we expect the prospective intern to leverage and extend. The final, key component of the internship is scientific contribution; the prospective intern is expected to work with teammates to publish a high-quality research paper in a major conference (AAAI, ECAI, ISWC, ESWC, IJCAI, etc.)
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By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
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