项目介绍

2024年5月8日

Your function

A 3-year full-time PostDoc student position is available at the Knowledge in Artificial Intelligence (KAI) group of the Vrije Universiteit Amsterdam, in close collaboration with ASML Veldhoven. The successful candidate will investigate Knowledge Representation and Engineering challenges as part of a close collaboration with ASML on the usage of knowledge intensive methods for Diagnostic Reasoning.

Diagnostics of large Cyber-physical systems is a highly complex process involving both (sensor and other quantitative) data about the machines, as well as rich sources of highly diverse knowledge, that comes in form of tribal knowledge, expert knowledge, design knowledge, documentation and formal specification, and present in numerous different modalities, such as texts, table, diagrams and very often simply in the heads and folklore of the experts. In order to reason about system failures, we need to model this knowledge formally to make it suitable for (diagnostic) reasoning.

In this project, which is a collaboration between the VU Amsterdam, the Universiteit van Amsterdam and ASML, the main challenges will be:

• to design an ecosystem of knowledge bases that model the respective information in the most suitable formalism, while providing maximal interoperability
• the construction of (consensus) vocabularies
• to combine the modelled and extracted formalised knowledge and to apply diagnostic reasoning to identify likely causes of a systems failure

While Knowledge Graphs and Ontologies will be good starting points from a modelling perspective we expect the reasoning methods that will be developed to require mixed and modular reasoning, possibly combining knowledge graphs with probabilistic or approximate reasoning given the diverse nature of the knowledge sources.

To maximally benefit from the collaboration between the academic and industrial partners, the successful candidate will spend about 50% of their time at ASML and 50% at the VU. 

Your profile

We are looking for a PostDOC candidate passionate about Artificial Intelligence, in particular knowledge representation & reasoning (KR&R). Knowledge of semantic technologies, formal methods, and applied (possibly probabilistic) logics is a plus, as is experience with diagnostics and the modelling of cyber-physical systems. Candidates are expected to have completed a PhD in Computer Science or Artificial Intelligence or a closely related field. 

The project is led by dr. Stefan Schlobach (Knowledge in AI group at VU Amsterdam)  

As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its complexity is invaluable for the quality of our teaching, research and service. We are always looking for talent with diverse backgrounds and experiences. This also means that we are committed to creating an inclusive community so that we can use diversity as an asset.

We realise that each individual brings a unique set of skills, expertise and mindset. Therefore we are happy to invite anyone who recognises themselves in the profile to apply, even if you do not meet all the requirements.