We are looking for a PhD student who will address scientific challenges in scalable reasoning on knowledge graphs and machine learning for semantic models in the domain of Internet of Things (IoT) and Smart Energy. In the context of the EU funded Interconnect project, several IoT solutions for smart homes will be integrated using Semantic technologies, bringing together data from users and devices in large knowledge graphs which includes ontologies such as SAREF. In order to deliver advanced data analytics on heterogeneous data, we will use and extend current machine learning methods to deal with multi-modal data (geo-data, sensor-data, background knowledge) , which are available as Knowledge Graphs through a semantic interoperability framework. Since the data analytics will be produced for a variety of human users, the models and solutions will have to deal with varying levels of user interaction and be able to provide insights into how and why certain analyses or even decisions were made. This type of explainable AI enables communicating results better to these users. The research is done in close collaboration with TNO (Data Science expertise group) as part of the European InterConnect project. The PhD position is located in Amsterdam, but will be seconded by TNO and the candidate will be expected to spend a part of the time at TNO Den Haag location.
Your duties

• perform  scientific research on extending and validating the SAREF ontology and other related ontologies as well as on distributed scalable reasoning for these ontologies
• perform scientific research on Machine Learning solutions on Knowledge Graphs, including user-centric (explainable) services
• validate the developed solutions through real-world experiments in one or more large pilots (one pilot is in Netherlands, Eindhoven) in collaboration with local and European project partners
• write scientific papers for international peer-reviewed conferences and journals
• present your work in international conferences
• finalise the work in a PhD thesis
• a limited amount of teaching (e.g., helping with a lab course, max 10% of your time)

• you have an Msc degree in Computer Science, Artificial Intelligence, Computational Science, Information Science or closely related area
• you are able and have the ability to work well in teams
• you do have expertise in Knowledge Representation/Semantic Web or Machine Learning/Deep Learning. PhD-level courses are available if one such expertise is missing
• experience in IoT or Smart Energy is an advantage
• proficiency in the English language

Fixed-term contract: 1 year.

A challenging position in a socially involved organisation. The salary is based upon 1 fte and will be in accordance with university regulations for academic personnel and amounts €2,325 (scale 85) gross per month during the first year and increases to €2,972 (scale 85) gross per month during the fourth year, based on a full-time employment. The job profile (promovendus) is based on the university job ranking system and is vacant for at least 1 FTE.

The appointment will initially be for 1 year. After a satisfactory evaluation of the initial appointment, the contract will be extended for a duration of 4 years.
Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• a maximum of 41 days of annual leave based on full-time employment
• 8% holiday allowance and 8.3% end-of-year bonus
• contribution to commuting expenses
• optional model for designing a personalised benefits package
• a wide range of sports facilities which staff may use at a modest charge

The ambition of Vrije Universiteit Amsterdam is clear: to contribute to a better world through outstanding education and ground-breaking research. And to be a university where personal education and societal involvement play a leading role. Where people from different disciplines and backgrounds work together on innovations and on generating new knowledge. Our teaching and research embrace the whole spectrum of science – from the humanities, the social sciences and the pure sciences through to the life sciences and the medical sciences.

Vrije Universiteit Amsterdam is home to more than 23,000 students. We employ more than 4,500 individuals. The VU campus is easily accessible, located in the heart of Amsterdam’s Zuidas district, a truly inspiring environment for teaching and research.

Diversity
Diversity is one of our university’s core values. We are an inclusive community, and we believe that diversity and international activities enhance the quality of education and research. We are always looking for people who can enhance diversity on our campus thanks to their background and experience.

The Faculty of Science
The Faculty of Science inspires researchers and students to find sustainable solutions for complex societal issues. From forest fires to big data, from obesity to medicines and from molecules to the moon: our teaching and research programmes cover the full spectrum of the natural sciences. We share knowledge and experience with leading research institutes and industries, both here in the Netherlands and abroad.

Working at the Faculty of Science means working with students, PhD candidates and researchers, all with a clear focus on their field and a broad view of the world. We employ more than 1,250 staff members, and we are home to around 6,000 students.
 
About the department, institute, projectThe VU Department of Computer Science has approximately 170 members, including 35 tenured staff members and 50 PhD students. Within the department, the Semantic Web group studies Knowledge Representation and User-centric data science, developing new  technology and testing it in real-world applications. TNO, the Netherlands Organisation for applied scientific research TNO was founded to enable business and government to apply knowledge. TNO’s Data Science department has expertise on sharing and analysing  structured and unstructured data. In a world where people and machines are becoming increasingly interconnected, data – both complex data and big data – is becoming increasingly important. Our primary mission is to understand and give meaning to this data, using an explainable, collaborative and responsible approach. The work is part of the Horizon2020 Interconnect project. Interconnect aims to democratize efficient energy management, through a flexible and interoperable ecosystem where distributed energy resources can be integrated with effective benefits to end-users. The project aims to design an interoperable marketplace toolbox supported by a novel IoT reference architecture that defines the interconnection between different digital platforms and aligning existing standards and ontologies like SAREF, allowing different stakeholders to develop  innovative services towards a human-centric energy ecosystem. The results will be validated through a number of large-scale pilots.