Department of Computer Science
Faculty of Science
University of Copenhagen
The Department of Computer Science, Faculty of Science at University of Copenhagen (DIKU) is offering a PhD scholarship in Computer Science and Communication commencing 01.01.2021 or as soon as possible thereafter. The position is offered jointly with the Department of Communication, University of Copenhagen (KOMM).
Description of the scientific environment
The University of Copenhagen was founded in 1479 and is the oldest and largest university in Denmark. It is often ranked as the best university in Scandinavia and consistently as one of the top places in Europe. Within computer science, it is ranked number one in the European Union (post-Brexit) by the Shanghai Ranking.
The working language of the university is English, and knowledge of English is also fully sufficient to navigate life in Denmark in general. Denmark routinely scores at the absolute top in rankings of quality of life such as e.g., the OECD Better Life Index http://www.oecdbetterlifeindex.org
The PhD student will be part of an interdisciplinary team consisting of computer scientists and media scholars, and will be embedded in a vibrant research environment consisting of colleagues from a broad background in both fields.
The Privacy Lost project uses web tracking (based on cookies and scripts embedded in websites) as a key exemplar of digital surveillance. By mapping the historical diffusion of web tracking through web archives, the project aims to make core elements and dynamics of digital surveillance visible. The ultimate aim of the project is to understand how the dynamics of tracking have been shaped by variations in economic, social and cultural factors across the globe, and how this in turn sheds light on the development of surveillance capitalism.
The engineers of some of the early web tracking companies were quick to realize how tracking could combine with machine learning and be monetized. The project uses the same tools to understand web tracking in a way that is at once fine-grained and large-scale. As part of the project, the historical top-thousands of web pages from all countries in the world will be harvested and classified automatically by genre and tracker types using standard methods from machine learning; the results will be further analyzed using methods from network analysis and information retrieval combined with state-of-the-art methods from media studies. The PhD fellow is expected to contribute to all phases of the project, whence applicants with prior experience both in computer science and media studies or similar fields are ideal.
The project will offer the selected PhD candidate an opportunity to participate in pioneering work on the development of surveillance capitalism, and to combine theories and methods from computer science and media studies.
Role of the PhD Student
The PhD fellow is expected to contribute to all phases of the project, whence applicants with prior experience in both computer science and media studies or similar fields are ideal. Tasks will include participation in development of experiments with collection and analysis of tracker technologies from archived and contemporary websites, setup and maintenance of project infrastructure needed for experiments, and application of machine learning and other standard techniques. Tasks will also include analysis of formation of tracker ecologies with contextual factors such as social and economic factors.
Principal supervisor is Professor Jakob Grue Simonsen, Department of Computer Science, email@example.com , Direct Phone: (+45) 35321439.
The PhD fellow will be jointly supervised by Professors Rasmus Helles (KOMM) and Jakob Grue Simonsen (DIKU), and will be joined by two post doc scholars working on the project. The PhD fellow is expected to partake, and co-author publications, in both traditional venues in computer science, respectively in media research, and at interdisciplinary venues.
The position is available for a 3-year period and your key tasks as a PhD student at SCIENCE are to:
- manage and carry through your research project
- attend PhD courses
- write scientific articles and your PhD thesis
- teach and disseminate your research
- stay at an external research institution for a few months, preferably abroad
- work for the department
Applicants should hold an MSc degree in a field relevant to the posting with good results and good English skills. Examples of relevant fields are: computer science, information studies, media studies, engineering, sociology, or political science. For non-computer science graduates, documented technical and mathematical/statistical competencies are required. As criteria for the assessment of your qualifications, emphasis will also be laid on previous publications (if any) and relevant work experience.
Desired applicants have mathematical maturity, good programming ability in a modern high-level language, an interest in understanding the wider social significance and embedding of surveillance technologies, and the social and economic factors that have shaped its development, as well as an interest interdisciplinary work that combines methods from diverse academic fields. In addition, prior experience in any of the following will be an advantage: Applied machine learning, information retrieval, natural-language processing, preferably in multiple languages, media systems analysis and/or comparative analysis of media regulation and economy, the surveillance economy and/or the social embedding of surveillance technology, the current state and historical development of web tracking technology, or contribution to interdisciplinary research.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.
The starting salary is currently at a minimum DKK 331,125 (approx. €43,750) including annual supplement (+ pension at a minimum DKK 53,811). Negotiation for salary supplement is possible.
The application, in English, must be submitted electronically by clicking APPLY NOW below.
- Cover Letter, detailing your motivation and background for applying for the PhD project.
- Diploma and transcripts of records (BSc and MSc)
- Other information for consideration, e.g. list of publications (if any)
- 1-3 reference letters (if any)
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
The deadline for applications is 23 November 2020 23:59 GMT +1.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. Afterwards an assessment committee will be appointed to evaluate the selected applications. The applicants will be notified of the composition of the committee and the final selection of a successful candidate will be made by the Head of Department, based on the recommendations of the assessment committee and the interview committee.
The main criterion for selection will be the research potential of the applicant and the above-mentioned skills. The successful candidate will then be requested to formally apply for enrolment as a PhD student at the PhD school of Science. You can read more about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .
For specific information about the PhD scholarship, please contact the principal supervisor Professor Jakob Grue Simonsen, Department of Computer Science, firstname.lastname@example.org , Direct Phone: (+45) 35321439.
General information about PhD programmes at SCIENCE is available at https://www.science.ku.dk/phd
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.
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