Master Thesis (m/f) Data Exploration Tool Industrial Plant Data

11 Jul 2016
29 Jan 2017
Contract Type
Full Time
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 application or development of data mining methodologies and technical features, to build up a data exploration tool for industrial plant data, addressing the specific challenges in the industry such as how to organize/correlate and search in unstructured data.

• You are a fully matriculated student in computer science or a related fields.
• You have experience in (big) data mining and data visualization concepts and technologies, such as Hadoop, Apache Solr, node.js, JavaScript, HTML5.
• Fluent command of German and English, both written and spoken.