The University of Copenhagen currently has open PhD Positions in Social Data Science to offer international students who have been dreaming of advancing their academic career in Denmark. Obviously, this program will be covering PhD level program(s) in the field of Data Science taught at University of Copenhagen only. The deadline is currently unknown. It is advisable to start your application process as soon as possible. Stay vigilant!
University of Copenhagen – About
The University of Copenhagen also known as UCPH is a state-owned academic institution in Copenhagen, Denmark. It is the 2nd-oldest university in Scandinavia, which was established in the year 1479. It is commonly regarded as one of the best in the Nordic nations and all of Europe as a whole.
The Academia is a research-centered institution higher learning that offers high level research and training services. The school takes part in notable international research partnerships, like the League of European Research Universities and the International Alliance of Research Universities.
The university maintains strong co-operative arrangements with private sector establishments like GlaxoSmithKline, Microsoft, Novo Nordisk, Novozymes and VELUX. Gifted scientists work together to move science novelties out of the lab and into society. Each year, UCPH also achieves about 800 agreements for teamwork with public and private institutions.
Why University of Copenhagen? During study at the University of Copenhagen, scholars will get solid professional opportunities, impressive academic ability, and cutting-edge skills for a successful future.
Through numerous reforms in the 18th and 19th century, the university was switched into a modern, secular university, with science and the humanities substituting theology as the major subjects studied and taught. It has 6 different faculties, with teaching occurring in its four distinct campuses, all spread across Copenhagen.
PhD Positions in Social Data Science – Summary
- Funding Type: Fully Funded (Good Salary package)
- Awarding Institution: University of Copenhagen
- Study Level: PhD
- Department: Data Science
- Eligible Students: International Students
Benefits of PhD Positions in Social Data Science
Recipients of PhD Positions in Social Data Science will be offered the benefits below:
- The program will offer a good salary package to successful applicants.
Eligibility for PhD Positions in Social Data Science
To be eligible for PhD Positions in Social Data Science, applicants must satisfy the requirements below:
- Eligible Nationalities: Allinternational students are fit to apply.
- Applicants should have experience working with (huge) data sets from former work as a research assistant or from personal research.
- A track history of solid academic performance.
- Experience from previous coursework in machine learning and econometric methods.
How to Apply for PhD Positions in Social Data Science
To avail PhD Positions in Social Data Science, please follow the guidelines below:
- To be selected for the funding opportunity, candidates must fill out and submit the online application form.
- Candidates are expected to become a part of the University of Copenhagen as a Ph.D. scholar at the Department of Biology.
- Necessary Documents: Applicants must provide documents in the manner below:
- Cover Letter – It hast to comprehensively detail applicant’s motivation and background for applying for the project.
- Ideas outline for projects under the frame of the entire project (potentially related to questions of resources allocated to daycare centers or starting age). The outline should detail potential ideas for identification approaches that are appropriate and critically deliberate challenges.
- Diploma and/or transcripts of records (BSc and MSc).
- Admission Prerequisites: Candidates must satisfy all entry conditions of the university.
- Language Prerequisites: If English language is not your first language, please present proof of English language ability: IELTS, TOEFL, or other acceptable proof.
To inquire further about PhD Positions in Social Data Science, please visit the official webpage.