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We seek to fill three 5-years PhD positions (full-time) on Learning Analytics, Collaborative and Social Computing and Parameterized Algorithms. The positions have 70% time allocated for research and 30% for teaching. This allows candidates to start developing a balanced academic career as independent researchers and competent teachers.
The task of a selected PhD candidate is to perform research on one of indicated topics, develop novel algorithms or software, validate them through well-designed experiments, publish the results at international conferences and in scientific journals, and complete a PhD thesis. Furthermore, the PhD candidate will contribute to teaching by supervising tutorial groups and student projects, and by co-teaching courses. This can possibly lead to a basic teaching qualification (BKO).
Topic 1: Learning Analytics
The candidate will join the Software Technology for Learning and Teaching group of Prof. Johan Jeuring to conduct research in the emerging field of Learning Analytics. This project will look into developing technologies, methods and tools that leverage large volumes of data generated by students working with online educational tools and resources to improve learning and teaching. The candidate will create and evaluate such tools under the supervision of Dr. Sergey Sosnovsky.
Topic 2: Collaborative and Social Computing
The candidate will join the Human-Centered Computing group of Prof. Judith Masthoff to conduct research in the field of Collaborative and Social Computing, and the related fields of Computer-Supported Cooperative Work and Crowdsourcing. This project will study the development of methods, algorithms and tools to enable large groups of people to collaborate efficiently from a distance on complex and creative tasks, with potential applications on open innovation, product design, gaming, and digital cultural heritage. The candidate will work under the supervision of Dr. Ioanna Lykourentzou.
Topic 3: Parameterized Algorithms
The candidate will join the Algorithms and Complexity group of Prof. Hans Bodlaender to conduct research in the field of Parameterized Algorithms. The project aims to discover new algorithmic methods and complexity lower bounds for graph problems, particularly coming from the area of network design. It requires background in techniques from parameterized algorithms, computational complexity, and graph theory. The candidate will work under the supervision of Dr. Erik Jan van Leeuwen.
Each successful PhD candidate is an excellent student and holds a Master degree in Computer Science, Information Science or a related field. Previous experience in one of the above topics would be a plus. Strong written and oral communication skills in English and interest in research and teaching in information or computer science are required.
Candidates of all nationalities may apply. The university is striving for gender balance in its research and teaching staff; hence, women are especially encouraged to apply for these positions. Applicants are encouraged to mention any personal circumstances that need to be taken into account in their evaluation (parental leave, military service etc.).
Selected candidates will be offered positions for 5-years (full-time). Salary starts at €2,325 and increases to €2,972 gross per month in the fourth year of the appointment. The salary is supplemented with a holiday bonus of 8% and an end-of-year bonus of 8,3% per year. In addition, we offer: a pension scheme, a partially paid parental leave, flexible employment conditions. Conditions are based on the Collective Labour Agreement Dutch Universities. The research groups will provide the candidates with necessary support on all aspects of the project. The positions are available immediately. More information is available on the website.
A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major societal themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.
The city of Utrecht is one of the oldest cities in the Netherlands, with a charming old centre and an internationally oriented culture that is strongly influenced by its century-old university. Utrecht city has been consistently ranked as one of the most liveable cities in the Netherlands.
The Faculty of Science consists of six Departments: Biology, Pharmaceutical Sciences, Information and Computing Sciences, Physics and Astronomy, Chemistry and Mathematics. The Faculty is home to 6,500 students and nearly 1,500 staff and is internationally renowned for the quality of its research. The Faculty's academic programmes reflect developments in today's society.
The Department of Information and Computing Sciences is nationally and internationally renowned for its research in Computing Science and Information Science. Current research groups are Algorithmic Data Analysis, Algorithms and Complexity, Decision Support Systems, Simulation of Complex Systems, Geometric Computing, Multimedia, Human-Centered Computing, Social and Affective Computing, Visualisation and Graphics, Interaction Technology, Process Management and Analytics, Organization and Information, Natural Language Processing, Intelligent Systems, Data Intensive Systems, Software Technology and Software Technology of Learning and Teaching. Relevant areas of interdisciplinary research include Game Research, Foundations of Complex Systems, Applied Data Science and Integrative Bioinformatics. The Department has, among others, close collaborations with the University Medical Center, the Departments of Physics and Mathematics, and the Faculties of Humanities and Geosciences.
The Department offers Bachelor programmes in Computer Science and Information Science, and four English language research Master programmes in Artificial Intelligence, Business Informatics, Computing Science, and Game and Media Technology. The Department is developing Master programmes in Data Science. High enrolment figures and good student ratings make the education very successful.