Researcher in analysis of events data

Event modelling concerns the analysis of ordered, timestamped data, with discrete states (or patterns) occurring at a particular point or points in the sequence. Examples include detecting faults or cyber-attacks in industrial processes and computer networks, predicting risk of fractures or disease flares in patients, learning of socio-political events through analysis of text data and even modelling the rate of taxi demand and hospital admissions.

We invite enthusiastic individuals to join our group at RPTU Kaiserslautern as a PhD student or postdoctoral researcher to work on a topic in this research area. Candidates should be interested in undertaking a project in the sphere of ’events data’, which includes one or a combination of the following sub-domains:

event detection
pattern recognition, anomaly and changepoint detection and process control: determining the occurrence events through recognizing patterns in historical data
spatio-temporal modelling
geographic information systems, survey data, epidemiology
event prediction
forecasting events, joint modelling of time-to-event and longitudinal data, modelling complex crises
causal event modelling
using structural models to answer counterfactual questions about the occurrence/non-occurrence of events

This project is a perfect fit for you if you have some experience in spatio-temporal modelling, statistical modelling, deep learning, and/or working with different data types.

If you would like to know more about this opportunity—both at PhD and at postdoctoral level—please get in touch.