PhD – Hybrid AI for Industry 4.0: Semantic Analytical Pipelines

Key Skills

Aartificial intelligence, C++, Effective communication skills, English Proficiency, Java Programming, Machine learning techniques, Presentation skills, Python Programming

Job Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

Artificial Intelligence (AI) is one of the central pillars of Industry 4.0 and Internet of Things in the global trend towards smart and highly-digitalized factories. An important approach here is to use symbolic AI, including ontologies or semantic Digital Twins, to represent experts’ knowledge, physical equipment and processes as unified conceptual Semantic Models. They in turn allow to integrate heterogeneous industrial data as uniform Knowledge Graphs. On top of ontologies and Knowledge Graphs, one can develop a wide range of AI solutions for production simulation, process monitoring, analytics and optimization. This can be achieved by combining symbolic reasoning and numeric AI methods, like Machine Learning, in hybrid AI solutions. Bosch Center for AI is active in developing such novel hybrid AI methods and systems and also in applying them in Bosch factories.

The purpose of this PhD research project is to develop (cloud) scalable analytical ML solutions powered with Semantic Models. For example, the PhD candidate can work on the development and implementation of semantic diagnostic or monitoring languages for equipment that allow one to express relevant analytical tasks as programs by combining ontological terms via a formal grammar, and continuously execute such programs over the equipment. Another example is ML models that allow to predict quality of discrete manufacturing operations where ontologies allow to integrate relevant data, formulate analytical tasks and parametrize ML pipelines behind the ML models. Semantic analytical pipelines in the context of Industry 4.0 allow for research topics that range from foundational to applied and give a great opportunity to do top-tier research and publish at top-tier venues as well as to test and evaluate novel techniques and methods in real industrial scenarios of Bosch.

PhD candidates will enjoy top quality inspiring research in an enthusiastic international environment of researchers, other PhD candidates, and industrial professionals from Bosch and its partners, in particular from the SIRIUS research centre at the University of Oslo and the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin.

Qualifications

• Education: excellent master degree in computer science (or related field)
• Personality: team player, self-motivated. inter-cultural, cross-domain proficiency,can-do attitute, good communication and presentation skills
• Working Practice: independently and within a team environment
• Experience and Knowledge:
• Profound experience in Knowledge Representation and Reasoning, in particular, Description Logics and ontology reasoning
• Experience with knowledge engineering and data integration
• Experience with machine learning and respective state-of-the-art toolkits
• Proven programming skills, e.g., Python/Java/C++
• Experience in writing scientific publications is a plus
• Languages: strong English, and academic writing skills