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Możliwość studiów doktoranckich w Zakładzie (EN)

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The Graduate School for Social Research (GSSR) is excited to offer a unique doctoral study opportunity within the Department of Computational Social Science (https://css.ifispan.edu.pl/en/the-department/) at IFiS PAN. Students will follow the GSSR PhD program and receive training in Computational Social Science, while working in a research team and fulfilling grant-related tasks. Students who opt for this opportunity will receive an additional stipend beyond the regular doctoral scholarship to support studies and research activities.

Details

  • Research Focus: Students will work on a project to combine traditional survey data with digital traces from online activities to provide new insights into social dynamics and human behavior. For details, see: http://rstyles.ifispan.edu.pl/wp-content/uploads/2021/02/SSDRL_opis_MARpdf.pdf.
  • Stipend: Starting October 2024, one selected candidate will be offered a stipend of 4.500 PLN/month, for up to 36 months. This net monthly sum is in addition to the regular doctoral stipend.

Candidate Profile

  • Educational Background: Applicants should possess a master’s degree in Sociology, Psychology, Political Science, Economics, Computer Science, or related fields with a strong interest in computational methods.
  • Skills: Proficiency in statistics, data science, machine learning, or computer science is highly desirable.
  • Research Interest: A keen interest in developing new lines of research at the intersection of social science and data science, particularly in studying digital footprints.
  • PhD plans: Students are required to plan their PhD studies within the framework of Computational Social Sciences ( https://css.ifispan.edu.pl/en/the-department/). They will do so under the guidance of senior faculty in the Department of Computational Social Sciences.

Why Apply?

  • Cutting-Edge Research: Tackle pressing societal issues like democracy dynamics and misinformation using advanced computational tools and big data.
  • Hands-On Learning: Gain practical experience with statistics, data science, and machine learning methodologies through involvement in research projects.
  • Career Flexibility: Prepare for diverse roles in both academic and commercial sectors, including data analytics, statistics, and machine learning.
  • Collaborative Opportunities: Participate in significant, multidisciplinary research endeavors, collaborating with experts across various fields to expand your professional network.

How to apply

In the Letter of Intent submitted as part of your application package to GSSR (see https://www.gssr.edu.pl/admissions/documents-checklist/), please indicate your interest in joining the Department of Computational Social Science at IFiS PAN. In addition to presenting your experience to date in your given discipline and your reasons for choosing GSSR/SNS as the site for doctoral training, please present your academic knowledge and skills, and academic interests and aims, that make you the right candidate for the Research Lab for the Digital Social Sciences project at the Department of Computational Social Science.

Evaluation

Applicants to GSSR’s doctoral program in Sociology who indicated their interest of joining the Research Lab for the Digital Social Sciences project and who successfully pass Stage 1 of the Admissions Process (see https://www.gssr.edu.pl/admissions/the-admission-process/) will be further evaluated, in terms of their fit to the grant project, during the second stage of the admission process to GSSR. A person who is not accepted to the Research Lab for the Digital Social Sciences project may still be accepted as a PhD student at GSSR, if their application ranks within the first seven places.

GSSR will communicate the results of the application for joining the Research Lab for the Digital Social Sciences project in IFiS’ Department of Computational Social Science together with the results of the Stage II evaluation outcomes. For more information, see https://www.gssr.edu.pl/admissions/important-dates/.