Liebe Kolleginnen und Kollegen, Colleagues,

für eine Weiterleitung an ggf. infrage kommende Kolleg/innen wären wir dankbar!

Thanks!

Betina Hollstein & Mario L. Small

The University of Bremen, U Bremen Excellence Chair Prof. Mario L. Small PhD/ Research Group "Large-Scale Data and Field Research in the Study of Social Networks" at the SOCIUM – Research Center on Inequality and Social Policy, invites applications for the following position

Post-Doctoral Researcher in Computational Social Sciences

German pay-scale EG 13 TV-L,

full time and limited until December 31, 2023 Start of contract: April 1, 2020 or earlier.

The University of Bremen, a mid-sized university with 320 professors, 19.500 students and a full-spectrum of academic disciplines is one of Europe’s leading research universities and maintains close cooperation with international universities and non-university research institutions in the region. The promotion of young researchers is a core element of Bremen's research strategy.

The 'U Bremen Excellence Chairs' program is a new initiative at University of Bremen since 2019. It enables internationally outstanding researchers to establish their own working groups at the university and to integrate them into a network of excellent research institutions worldwide in their respective disciplines. Mario L. Small's research group will study “Large-Scale Data and Field Research in the Study of Social Networks.” One major promise of “big data” was the ability to understand how social networks emerge, operate, and shape human behavior on a much larger scale than previously possible. However, as wide-eyed enthusiasm has given way to sober analysis, researchers and the public have become increasingly aware of the limitations of such data. This project will examine the extent to which field-based research (interview and survey research) can help address the limits of computationally intensive analysis of large-scale administrative data. Focusing on problems such as boundary specification, locality of interaction, algorithmic confounding, and misinterpretation of meaning, we will examine the extent to which bringing field research to bear on the analysis of large-scale administrative data can help improve our understanding of the relationship between networks and social inequality.

The postdoctoral researcher will help design, execute, and write the results of research bringing field methods to bear on large-scale, administrative data analysis.

Requirements:

* expertise in social science computational methods and the management of large datasets, either expertise or demonstrated familiarity with research in social networks, and a completed Ph.D. degree in either sociology or a related social science.

* demonstrated evidence of initiative, independence, drive, efficiency, productivity, the ability to work in groups, and a commitment to high quality social science research.

* high level of proficiency in English (including demonstrated academic writing skills), proficiency in German is welcome, but not required.

* experience with working in international projects, organizing academic events, and developing project proposals, preferably shown through employment, fellowship, or extended research stay at an international research institution within the past five years, is preferred but not required.

* strong interest in developing connections with other researchers; experience gained at other national/ international research institutions is welcome.

The researcher will also oversee a Ph.D. student at U Bremen who will conduct qualitative research. The postdoctoral researcher need not have direct expertise in qualitative interview methods or in survey methods, but some exposure to both methods is preferred.

Salary and benefits are linked to the German employee scale TVL13 (100%). International candidates are highly encouraged to apply.

The review process will begin on February 25, 2020. Applications and inquiries should be sent electronically as pdf-attachment by February 24, 2020 with the reference number A386/19 to mailto:socium-bewerbungen@uni-bremen.de socium-bewerbungen@uni-bremen.de

Applications will be reviewed until the position is filled.

Please note that the application should be submitted in English and that we can only accept it if it includes all required documents as a single PDF file: CV (with publication record), academic certificates, a sample chapter of your PhD thesis or other written paper, and a cover letter describing your background, interests, and motivation for applying. The application letter should also contain information about the data set(s) you have worked with.

The University of Bremen has received a number of awards for its gender and diversity policies and is particularly aiming to increase the number of female researchers. Applications from female candidates, international applications and applications of academics with a migration background are explicitly welcome. Disabled persons with the same professional and personal qualifications will be given preference.

For further information please contact Prof. Mario L. Small, PhD ( mailto:mario_small@harvard.edu mario_small@harvard.edu) or Prof. Dr. Betina Hollstein ( mailto:betina.hollstein@uni-bremen.de betina.hollstein@uni-bremen.de)

Prof. Dr. Betina Hollstein University of Bremen SOCIUM - Research Center on Inequality and Social Policy, Head Mary-Somerville-Str. 9, R. 9.3090 D - 28359 Bremen

tel +49 (0)421-218-58512 / 218-58638 (secr. Ms. Neumann) e-mail: betina.hollstein@uni-bremen.de mailto:betina.hollstein@uni-bremen.de http://www.socium.uni-bremen.de/about-the-socium/members/betina-hollstein/en /?

QUALISERVICE– Research Data Center for Qualitative Social Science Research Data, Head https://www.qualiservice.org/de/ - relaunch!

Recent publications:

https://www.socium.uni-bremen.de/ueber-das-socium/mitglieder/betina-hollste in/publikationen/?publ=8749 What autobiographical narratives tell us about the life course. Contributions of qualitative sequential analytical methods, in: Advances in Life Course Research, online-first (18.12.2018), http://dx.doi.org/10.1016/j.alcr.2018.10.001 doi:10.1016/j.alcr.2018.10.001

Collecting egocentric network data with visual tools. A comparative study, in: Network Science, forthcoming (with T. Töpfer & J. Pfeffer)