Description

Law enforcement constitutes an essential institution of the public sector that is going through a gradual transformation by applying digital strategies to improve its efficiency and effectiveness to predict events and automate work in crime deduction in several countries. The use of data-based innovations in police work has raised considerable attention in policy, media, legal, and academic debates. But we know very little about how big data is adopted and adapted in law enforcement activities and to what consequence. Moreover, data analytics's proliferation brings into question how citizens' rights are being protected as what counts as 'safety' or 'policing' is being fundamentally transformed, as well the understandings of social diversities these solutions are addressing.

The project financed by NordForsk aims to investigate how institutional and social values, digital affordances, and organizational politics are conceived and embedded in data-based police innovations and experienced and practiced by police officers and developers of digital police infrastructure.

There are three key inter-related research themes we are interested in (but not necessarily limited to these) and believe will crucially structure governance of social diversities through data in the coming years:

• Profiling in predictive policing, using the example of gene data. As the DNA genealogical databases are a valuable source for police, there are no universal rules in using these data in predictive policing. The potential understandings of the use of genetic data for predictive policing purposes and international police regulations of genetic biohacking, individuals' experimentations with their symbolic and physical (boundaries), are to be examined.
• Digital migration control through data. The digital migration (e.g., enabled by Estonian eresidency) has no physical residency assumption, but traditional migration policy's selectivity principles tend to be implemented in the policy instruments. The predictive datafied police solutions are implemented for classifying the applicants, but the selection mechanisms are not known.
• Automated solutions for predictive border control. The legal agencies implement facial recognition algorithms to identify travelers crossing the borders, classify wanted criminals, and predict crimes. The understanding of the social diversities of the human decision-makers who use the predictive border control tools is unknown.

Responsibilities and tasks

The researcher should design, develop, and complete his / her research results in peer-reviewed articles published in internationally recognized journals during the doctoral research. The research plan should also be in line and contribute to the strategic research axes of the Nurkse Department and its members. The ideal ratio between autonomous, independent research and the contribution of upcoming PhD students to joint research with other members of the Department is 50-50. As part of his / her path, the PhD student is also expected to gain teaching, supervision, and research management experience at the Nurkse Department. In this respect, courses, workshops, seminars, and inductions will be provided, to which new researchers are encouraged to attend and contribute. 

Qualifications

A successful candidate should preferably have:

• A MA degree in social sciences (preferably in sociology, public administration, media and communication studies, or social psychology) or in other areas with additional proof of social science research skills;
• Expertise in qualitative or quantitative, digital or computational research methods; knowledge in or readiness to use experimental study design and cognitive methods (eye-tracking, EEG / fNIRS) is an advantage;
• A clear interest in (and a neat vision for) independent research concerning the chosen topic; • Excellent command of English and Estonian languages;
• Strong and demonstrable writing and analytical skills;
• Capacity to work both as an independent researcher and as part of an international team;
• Ability and willingness to assist in organizational tasks relevant to the project.

We offer

• Up to a 4-year doctoral position at TalTech, one of the largest, internationally-renowned, and leading social sciences research centers in Estonia with a broad portfolio of ongoing pan-European and national projects in data studies, public administration, digital governance, and innovation studies projects.
• Involvement in R&I activities with founding partners of the projects and other key stakeholders (e.g., cities).
• Opportunities for conference visits, research stays, and networking with globally leading universities and research centers in the fields of data studies, public administration, innovation studies, and digital government.
• Ph.D. positions are guaranteed a net monthly income of 1200EUR (including 660EUR Ph.D. scholarship) and Estonian national health insurance).
• The first two years of the position will be financed by the NordForsk grant ('Critical understanding of predictive Policing').

About the organization

The Ragnar Nurkse Department of Innovation and Governance (RND) is an interdisciplinary, international research center within Tallinn University of Technology hosting world-renowned award-winning scholars and focusing on socially relevant research and teaching. Notably:

• Digital transformation of societies: social datafication, algorithmic governance, data justice, state-citizen relations in the digital era, smart cities and cross-border data relations;
• Models and practices of e-governance and public administration globally;
• P2P technologies, its governance, and potential new production models; • Fiscal governance and fiscal bureaucracies;
• Science and innovation policies and its management;
• Philosophy and ethics of science and technology.

RND is a highly internationalized department and engages some top international thinkers and researchers in its research fields. Next to a fully English taught Ph.D. degree, it offers a MA degree in Technology Governance and Digital Transformations and a unique Erasmus Mundus joint MSc program in Public Sector Innovation and e-Governance (PIONEER) in cooperation with KU Leuven (Belgium) and University of Münster (Germany). RND and its staff have coordinated or been involved in a multitude of international research projects with the EU (INTERREG, COST, FP7, H2020), UN (UNDP), OECD (SIGMA), INET. Department has participated in various European Commission working groups (the EU's Lisbon Agenda Group, Expert Group on Managing Risks in Public Technology Procurement, Expert Group on Public Sector Innovation).

Recently RND initiated a major, 32 MEUR international R&D project on Smart Cities (FinestTwins) and coordinated the H2020 funded large-scale innovation pilot on implementing the Once-Only Principle (TOOP), which laid the foundation for the data exchange layer foreseen in the European Single Digital Gateway Regulation (SDGR). RND is also engaged in several international associations, such as the European Master in Public Administration program (EMPA), European InterUniversity Association on Society, Science and Technology (ESST), and the European Group for Public Administration (EGPA), where RND coordinates the Permanent Study Group on Public Administration, Technology and Innovation.

Admission

To apply for this position, please submit:

• A one-page cover letter explaining the motivations;
• a CV with necessary certificates;
• a maximum of 5 pages of a research proposal

Please send all the relevant papers to Assoc Prof. Anu Masso (anu.masso@taltech.ee). If necessary, the Admissions Committee may request additional documents such as proof of the candidate's methodological and analytical skills (e.g., research article, study report, etc.)

Additional information

• For further information, please contact Assoc. Prof. Anu Masso (anu.masso@taltech.ee).
• The thesis will be supervised jointly by Assoc. Prof. Anu Masso (main supervisor), and Prof. Ahti-Veikko Pietarinen (co-supervisor).
• To get more information about the project, please see: https://cuppresearch.info/
• To get more information about the team, visit https://taltech.ee/datalab
• To get more information about the Nurkse Department, visit http://ttu.ee/nurkse