Ph.D. position in Situational Analytics

Last modified: 
Monday, September 14, 2015 - 17:15

In collaboration with TNO, the Department of Computer Sciences is seeking candidates for a Ph.D. position in Situational Analytics (f/m).

Situational Analytics is a new area of research that is focused on delivering a comprehensive awareness of a situation coupled with analytics to increase effectiveness and efficiency of decisions and actions. It is also the ability to rapidly evaluate past trends and present circumstances even as they are changing, with a focus on analyzing data that is relevant to a particular decision over time. 

The aim of the PhD project is to develop methods and technologies to filter, combine and interpret the vast amounts of information coming from various sources, such as (autonomous) sensors, in order to continuously provide up to date situational awareness tailored to the context of the person/role/organization at hand. 

In the desired situation, many data sources, (autonomous) sensors (including humans) provide a diverse and immense set of information. All this information is then gathered, filtered and pre-assessed autonomously in such a way that the situational awareness of the requestor is as rich as possible, and relevant to the decision at hand. 

The project will answer the following research questions: 

  • How can, in an automated way, real-time (sensor) information from various sources be combined, assessed and presented using situational analytics methods to create a comprehensive situational awareness; 
  • How can, in an automated way, real-time (sensor) information be used to calculate risks & opportunities and predict future situations to support effective and efficient decision making; 
  • How can, in an automated way, (sensor) information be tailored to a specific context/person, and how can this context be derived. 

The position will be financed through VU Amsterdam University (VUA) by TNO. The PhD student will be jointly supervised by TNO and the Computational Intelligence research group at VU. The student will work at both VUA and TNO offices, dividing the working time ca. 50/50. 

For more information, see the announcement at the VU website