As a PhD candidate, you will primarily address the following four topics: (1) planning & scheduling (2) prescriptive quality (3) predictive maintenance and (4) hybrid intelligence. These PhD positions are part of the Green Transport Delta, a public-private innovation programme (funded by the Dutch Ministry of Economic Affairs and Climate) that aims to make Dutch transport sectors futureproof and sustainable. You will be embedded in the consortium around electrification, which focuses on improving various aspects of battery-powered electric transport as a key component of the transition to climate-neutral mobility. In a joint collaboration with VDL Nedcar, the largest Dutch automotive manufacturing company, you will work in a team to investigate AI techniques within VDL Nedcar's manufacturing environment. The ultimate goal is to make intelligent decisions in a transparent and reliable way, reduce costs, and save energy and reduce overall CO2 emissions.

We are the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University, the Netherlands: an international community of 50 researchers at various stages of their career, embedded in the Faculty of Science and Engineering (FSE). Our department has nearly 30 years' experience with research and teaching in the fields of Artificial Intelligence, Computer Science and Mathematics, and we do so in a highly collaborative and cross-disciplinary manner. To strengthen our team, we are looking for a full professor who will work on AI systems that interact intelligently – and in a human-centered and responsible way - with other AI systems, humans, or both. Our department is growing rapidly. This position is one of multiple job openings: you are more than welcome to browse through our other vacancies.

We are the Department of Data Science and Knowledge Engineering (DKE) at Maastricht University, the Netherlands: an international community of 50 researchers at various stages of their career, embedded in the Faculty of Science and Engineering (FSE). Our department has nearly 30 years' experience with research and teaching in the fields of Artificial Intelligence, Computer Science and Mathematics, and we do so in a highly collaborative and cross-disciplinary manner. To strengthen our team, we are looking for a full professor who will work on AI systems that are able to explain the decisions and actions they recommend or take in a human-understandable way. Our department is growing rapidly. This position is one of multiple job openings: you are more than welcome to browse through our other vacancies.

We have nearly 30 years' experience in research and teaching. Our efforts focus on four complimentary fields: Artificial Intelligence, Data Science, Computer Science and Applied Mathematics. The department's contributions to areas such as multi-agent systems, (medical) signal and image processing, game theory and AI search techniques are internationally recognized. DKE maintains a large and worldwide network of public and private collaborators, and our staff is firmly rooted in multiple national and international research networks. Next to our research, we take pride in our education.

Creating official, high-quality statistics based on big data and register data is not a simple matter. The data sources were not designed for statistical use and safeguarding the quality and continuity is quite complex. Therefore, the ultimate challenge for data scientists is to develop methods that'translate' huge amounts of data into high-quality statistics. CBS pursues this challenge with methods such as machine learning. As CBS data scientist Marc Ponsen explains, 'Machine learning has received an enormous boost by faster computers and the huge amounts of data that have become available, although what the best possible method is very much depends on the domain under investigation.'

Work with other developers and data scientists to code proof-of-concept projects on large scale data sets. Develop data processing and system integration applications. Construct web based user interfaces and visualizations. Quickly ingest new technologies to consider applicability to current or future needs. Utilize statistics and predictive analytics to create innovative solutions to business problems.