An important but under-explored problem in computer science is the automated analysis of conversational dynamics in large, unstructured social gatherings such as networking or mingling events. Unlike analysing small, pre-arranged conversations, during mingling, sensor data is seriously contaminated. Moreover, determining who is talking with whom is difficult because groups can split and merge at will. A fundamentally different approach is needed to handle both the complexity of the social situation as well as the uncertainty of the sensor data. The successful applicant will develop novel techniques to quantify the quality of conversations from multi-sensor data (video, acceleration, audio, etc.) such as involvement and rapport. For information about the TU Delft Graduate School, please visit www.phd.tudelft.nl.

We are looking for students who have recently completed or expect to complete very soon an MSc or equivalent degree in computer science, electrical/electronic engineering, applied mathematics, applied physics, or a related discipline. Experience in the following or related fields are preferred: signal/audio/speech processing, computer vision, machine learning, and pattern recognition. Some experience with embedded systems is a bonus, though not necessary.

The successful applicants will have:
• good programming skills;
• curiosity and analytical skills;
• the ability to work in a multi-disciplinary team;
• motivation to meet deadlines;
• an affinity with related social science research;
• good spoken and written communication skills;
• an interest in communicating their research results to a wider audience;
• proficiency in English.

Fixed-term contract: 4 years.

The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit graduateschool.tudelft.nl/ for more information.

For more information about this position, please contact Hayley Hung, h.hung@tudelft.nl. Interested applicants should send an up-to-date curriculum vitae, degree transcripts, letter of application, and the names and the contact information (telephone number and email address) of two references to Hr-eemcs@tudelft.nl with the subject heading '[MINGLE PhD]'. The letter of application should summarise (1) why the applicant wants to do a PhD, (2) why the project is of interest to the applicant, (3) evidence of suitability for the job, and (4) what the applicant hopes to gain from the position.

The application procedure is ongoing until the position is filled, so interested candidates are encouraged to apply as soon as possible and before January 12 2018. Note that candidates who apply after this deadline may still be considered but applications before the deadline will be given priority.

When applying for this position, please refer to vacancy number EWI2017-21.

Delft University of Technology

Delft University of Technology (the TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. The TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At the TU Delft you will work in an environment where technical sciences and society converge. The TU Delft comprises eight faculties, unique laboratories, research institutes and schools.

http://www.tudelft.nl

Electrical Engineering, Mathematics & Computer Science

The Department of Intelligent Systems (INSY) conducts research on processing, interpretation and securing of data. Our aim is to enable man and machine to deal with the increasing volume and complexity of data and communication. We have a strong focus on security, multimedia, and health sciences. The Department pursues its mission by combining fundamental research, engineering and design approaches to model- and knowledge-based methods and algorithms. We actively seek research and technology-transfer collaboration with international scientific peers, companies, and societal organisations.

The Pattern Recognition and BioInformatics Group is one of five groups in the department, consisting of seven faculty members and over 20 post-doc and PhD students. Within this group, research is carried out in three core subjects: pattern recognition, computer vision, and bioinformatics. One of the main focuses of the group is on developing tools and theories, and gaining knowledge and understanding applicable to a broad range of general problems, but typically involving sensory data, e.g. time signals, images, video streams, or other physical measurement data.