We will support you in the final phase of your master's degree course. Compile your practically-oriented thesis with us, and seize the opportunity to gain insights into an international group. ABB will provide you with wide-ranging, professional and expert support to bring your thesis to a successful conclusion. The financial support we can offer includes a utilisation bonus for your thesis.
A typical industrial plant, such as a petro-chemical plant, generates a large amount of data every year: measurement values, alarm and event logs, laboratory results, maintenance reports, and so on.
The amount of data gathered can easily sum up several hundreds of gigabytes per year, resulting in truly big data. The availability of such historic data makes big data analytics and technologies interesting also for the industrial domain. In our BMWF public funded project "FEE", ABB Corporate Research is collaborating with industry and university partners to develop such concepts for big data analytics for industrial plants.
The objective of your master thesis will be the development of (big) data analytics algorithms and methodologies to enable building a search engine that will allow plant operators to search their historic plant data for information related to their current plant situation, e.g. searching whether a given plant situation has already happened in the past in a similar way.
• You are a fully matriculated student in computer science or a related fields.
• You have experience in data mining approaches, such as correlation analysis and signal analysis, as well as development languages such as R, Matlab, C#, or Java.
• Fluent command of German and English, both written and spoken.