Phd Position in Eindhoven University of Technology, Netherlands

The Eindhoven University of Technology (TU/e) has the following vacancy PhD student 'COMPASS' project(V32.045) at Databases and Hypermedia Department of Mathematics and Computer science

The Department of Mathematics and Computer Science provides undergraduate and MSc programs in Mathematics and in Computer Science. The department has research collaborations with other departments at the Technische Universiteit Eindhoven as well as with a large number of other universities and companies, both at home and abroad. The Department has approximately 350 employees and more than 700 students.

The Databases and Hypermedia group is world-leading in the area of adaptive hypermedia and adaptive web-based information systems. The group has produced the most referenced reference model for adaptive hypermedia and developed the most popular general-purpose adaptive hypermedia system AHA!. The group has expertise in data mining, web engineering and semantic web, and also works in application fields for adaptive technology, including e-learning and e-culture. The group has ample experience in national and international research projects, both as participant and as coordinator.

Tasks

The COMPASS project (Complex Patterns in Streams), funded by NWO in the open competition program, is a cooperation between the data mining groups of LIACS (Leiden Institute of Advanced Computer Science) at Leiden University and DH (Databases and Hypermedia) at TU Eindhoven. The goal of the project is the development of stream mining techniques for complex patterns such as graphs.
A short summary of the project:
In recent years there has been a growing interest in the study and analysis of flows of so-called data streams. Typical examples of such streams include Internet traffic data and continuous sensor readings. Traditional data mining approaches are not suitable for mining such streams, because they assume static data stored in a database, whereas streams are continuous, high speed, and unbounded. Therefore, streams must be analyzed as they are produced and high quality, online results need to be guaranteed.
Until now, most pattern mining techniques focus either on non-streaming data, or only consider very simple patterns, such as identifying the hot items from one stream, or constantly maintaining the frequencies in a window sliding over the stream. The challenging task we set forward in this project is to extend the existing state-of-the-art techniques into two, orthogonal directions: on the one hand, the mining of more complex patterns in streams, such as sequential
patterns and evolving graph patterns and on the other hand, more natural stream support measures taking into account the temporal nature of most data streams. The developed techniques will be tested on real-life data, such as social network data and the World-Wide Web. Next to those datasets, in the project we will have access to the data streams generated by a sensor network mounted on a large bridge in The Netherlands.

As PhD Student, you will:

• perform scientific research;
• present results on international conferences;
• publish results in scientific journals;
• participate in activities of the group and of the department.

Requirements

We are looking for a candidate who meets the following requirements:

• a MSc degree in Computer Science, Mathematics or a closely related field;
• interest in knowledge discovery and machine learning;
• good programming skills;
• good communication and writing skills in English.

Appointment and Salary

We offer:

• a full-time employment for 4 years with an intermediate evaluation after 1 year;
• a salary of € 2,042 per month (gross) in the first year, increasing to € 2,612 per month (gross) in the fourth year. Moreover 8% holiday allowance and 8.3 % end-of-year bonus is provided annually;
• support with your personal development and career planning;
• a broad package of fringe benefits (e.g. excellent technical infrastructure, child care, savings schemes, and excellent sports facilities).

Information

More information:

• Information about the project and the DH group at TU/e: Dr. T.G.K. Calders, e-mail: t.calders@tue.nl
• Information about the job conditions: Mrs. P.J. Evers, HR advisor, email: pzwin@tue.nl

Application

Interested candidates are requested to send their application by e-mail to: pzwin@tue.nl

The application should consist of the following parts:

• a curriculum vitae;
• an explanation of your interest in the proposed research field;
• a complete list of attended courses and corresponding grades, references, and all other information that might be relevant;
• proof of English language skills (if applicable).

Please include the job vacancy code: V32.045

You can apply for this job before 15-09-2009