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University of Arkansas at Little Rock

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Postdoctoral Fellow in Computational Social Science, Cyber Campaigns, and Social Media Analytics University of Arkansas at Little Rock in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time, benefits-eligible provisional postdoctoral position funded through a grant or contract. Renewal depends on continued grant funding and satisfactory job performance. Salary is $85,000 annually. Sponsorship is not available.

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Country

United States

University

University of Arkansas at Little Rock

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Keywords

Computer Science
Data Science
Information Technology
Communication Studies
Political Science
Network Analysis
Artificial Intelligence
Natural Language Processing
Computational Social Science
Computational Modelling
Statistics
ML

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About this position

The COSMOS Research Center at the University of Arkansas at Little Rock is seeking a full-time Postdoctoral Fellow II to advance computational social science research on cyber campaigns conducted through social media.

Working with Prof. Nitin Agarwal and the COSMOS research team, the fellow will develop socio-computational models grounded in social and communication processes such as group formation, activation, decentralized decision-making, and collective action. The research involves extracting open-source information through guided snowball data collection, cyber forensics, and deep-web search methodologies.

The fellow will analyze text, multimedia-rich online environments, and social networks to identify patterns, trends, key actors, and groups involved in coordinating cyber campaigns and disseminating propaganda. Research activities include data collection, cleaning, preprocessing, modeling, interpretation, and the development of predictive models for socio-technical behaviors across social media platforms.

The position combines research with practical tool building. The fellow will develop software modules and usable applications, contribute to publications, reports, conference presentations, grant proposals, and technical documentation, and provide training and technical assistance to stakeholders. The role also includes mentoring graduate students, coordinating multidisciplinary research meetings, managing project activities, and collaborating with researchers and data engineers.

The research environment uses data science, machine learning, artificial intelligence, natural language processing, text mining, graph analytics, social network analysis, and multimedia analysis to study complex online information ecosystems and cyber behavior.

Funding details

Full-time, benefits-eligible provisional postdoctoral position funded through a grant or contract. Renewal depends on continued grant funding and satisfactory job performance. Salary is $85,000 annually. Sponsorship is not available.

What's required

A Ph.D. in Computer Science, Information Science, or a related discipline is required, along with at least two years of research experience in social media mining, computational modeling of social science theories, social network analysis tools, and cyber campaigns on social media, demonstrated through publications in leading relevant journals and conferences. Preferred qualifications include extensive computer programming and data-management experience, grant-writing experience, a strong publication record, research methodology and statistical-analysis knowledge, experience with NLP, text mining, graph analytics, machine learning, AI, multimedia social-media content, and translating research outcomes into usable tools. Candidates should have strong oral and written communication, collaboration, mentoring, organizational, project-management, and independent-working skills. Legal authority to work in the United States on the first day of employment is required; pre-employment criminal background and sex-offender-registry checks apply.

How to apply

Apply through the University of Arkansas System Career Site by selecting the Apply button for this posting. Upload a resume, letters of recommendation, a publication list, and a list of three professional references including each person’s name, email, and business title. Do not send application materials to the recruitment contact.

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