Two postdoctoral positions, EMERGEPOL (ERC Advanced Grant), Koç University, Istanbul. Starting January 2027, I am recruiting for a five-year comparative project on how new political issues — migration...

Strengthen your research with practical statistical skills. The 5-day online “Introduction to Research Methods and Statistics” workshop from the Centre for Applied Statistics Courses (CASC) at University College London is designed for PhD students, academics and professional researchers across disciplines. Build confidence in data visualization, experimental design, hypothesis testing, regression, multivariate analysis, statistical software and reproducible research through a blend of theory and hands-on learning. Join live via Zoom or choose the on-demand option, with seminar materials available for 30 days and an instructor-monitored forum for questions. Participants receive an Instats certificate of completion, with ECTS equivalent points available for European students. Explore the workshop and take your research skills further. #ResearchMethods #Statistics #PhD #AcademicResearch #ProfessionalDevelopment #Demography #ComputerScience #StatisticsEducation #Business #ComputationalStatistics #HealthEconomics #SocialSciences #InformationSystems #PopulationBiology #ComputationalSocialScience #DigitalHumanities #History #Statisticalmodellingandregression #CulturalEconomics #PublicHealth #Education #Epidemiology #Biostatistics #Statistics #DataScience #Economics #Research #ResearchTraining #Instats

Move beyond prediction and learn how to answer the question: what causes what? Join this intensive two-day online workshop in causal inference for PhD students, researchers, practitioners, and policymakers. Build practical skills in study design, causal identification, RCTs, instrumental variables, difference-in-differences, Double Machine Learning, and causal forests—with hands-on R examples and LLM-assisted tools for diagnostics, robustness checks, and communicating results. You’ll learn to assess assumptions, address threats to validity, and interpret treatment effects while keeping programming overhead low. Live sessions are held on Zoom, with recordings and materials available for 30 days, instructor support through an online forum, take-home challenges, and an official certificate of completion. Basic statistics or regression knowledge is helpful, but no advanced programming experience is required. #ComputationalSocialScience #DataAnalytics #DataScience #Economics #PublicPolicy #Statistics #Econometrics #ComputerScience #RStudio #ChatGPT #ClaudeCode #Claude #Research #ResearchTraining #Instats

Could geography change your research conclusions? Join our free, 90-minute online seminar for PhD students, postdocs and researchers to explore why location, neighbourhood effects and territorial boundaries matter for rigorous social science. This guided, code-free showcase brings spatial thinking to life through finished maps, published studies and real examples of electoral behaviour, policy diffusion and place-based inequality. Discover when spatial analysis can strengthen your research—and see how R can serve as a complete Geographic Information System (GIS), not just a statistics tool. No coding experience or prior GIS knowledge is needed. Attend live via Zoom or watch the recording, with 30-day access to seminar materials and an expert-monitored Q&A forum, plus a certificate of completion. Take your first step beyond descriptive mapping and discover what geographic thinking could reveal in your research! #AppliedResearch #ComputationalSocialScience #DataAnalytics #DataScience #Economics #Geography #PoliticalScience #QuantitativeMethods #ResearchMethods #Scientificprogramming #SocialSciences #SpatialData #Statistics #PublicPolicy #Sociology #R #Research #ResearchTraining #Instats

Ready to take your social network research beyond descriptive metrics? Join Antonio Zinilli for an advanced, hands-on online seminar on social network analysis using RStudio, designed for PhD students, postdoctoral researchers, and established social scientists. Learn to prepare relational data, compute and interpret centrality measures, create publication-quality network visualisations, and connect network patterns to substantive research questions. A real-world case study and an introduction to Exponential Random Graph Models (ERGMs) will help you build a rigorous, reproducible workflow for dissertations, publications, and collaborative projects. Attend live via Zoom or learn asynchronously, with recordings, materials, and expert-monitored Q&A available for 30 days after the seminar. An official Instats certificate of completion is included. #SocialNetworkAnalysis #RStudio #PhD #ResearchMethods #ComputationalSocialScience #ComputationalSocialScience #ComputationalStatistics #Criminology #DataAnalytics #DataScience #Demography #NetworkAnalysis #PoliticalScience #QuantitativeMethods #ResearchMethods #SocialNetworkAnalysis #SocialPolicy #SocialPsychology #SocialSciences #SocialStratification #Sociology #Statistics #RStudio #Research #ResearchTraining #Instats

Want to make your data analysis more efficient without compromising research rigor? Join Dr Kimberly Fessel for a one-day, hands-on online seminar on using ChatGPT alongside Jupyter and Python in research workflows. Designed for PhD students, postdocs, faculty, and research professionals with basic familiarity with Python and statistics, the workshop covers data cleaning, exploratory analysis, coding and debugging, visualization, and synthetic data generation. You’ll also practice validating AI-generated outputs, keeping your work reproducible, and protecting sensitive data—using AI as an assistant, not a substitute for your expertise. Attend live via Zoom or revisit the recording and materials for 30 days afterward, with access to an expert-monitored Q&A forum. #ArtificialIntelligence #ComputationalSocialScience #DataAnalytics #DataScience #Statistics #ComputerScience #InformationScience #SoftwareEngineering #ChatGPT #Jupyter #Python #Research #ResearchTraining #Instats

VideoParl is a DFG-funded research project analyzing text, audio and video from German parliamentary debates.

Political and social scientists are working with more text than ever, from parliamentary speeches and treaty preambles to government reports, news coverage, social media posts, and policy documents. This 3-day intensive online seminar shows PhD students and professional researchers how to use large language models to turn complex text into defensible, analysis-ready data without requiring prior machine learning or Python experience. Through live Google Colab demonstrations, participants will learn when to use encoder models such as BERT and DeBERTa, when generative models such as GPT or Claude are more appropriate, how to apply zero-shot classification, build and validate gold-standard datasets, evaluate performance with metrics such as accuracy, F1 scores, Cohen’s kappa, and confusion matrices, and create end-to-end pipelines for extracting and cleaning data from PDFs, websites, and other messy sources. The seminar is designed to help researchers strengthen methodological credibility, accelerate data collection and coding, and expand the range of research questions that can be tackled with text. All sessions are livestreamed via Zoom, with recordings, slides, code, data, and a monitored Q&A forum available for 30 days after the seminar, plus an official Instats certificate of completion. #ArtificialIntelligence #ComputationalSocialScience #PoliticalScience #ComputerScience #Statistics #DataScience #InformationScience #SocialTheory #Sociology #Claude #GoogleColab #HuggingFace #Jupyter #Python #Research #ResearchTraining #Instats

Social networks are essential for studying diffusion, influence, segregation, cooperation, inequality, and many other relational processes — but analyzing network data well requires methods that account for dependence, structure, measurement, and privacy. Join our one-day online workshop, Modern Statistical Methods for Networks, led by Professor Tianxi Li from the School of Statistics at the University of Minnesota, Twin Cities, for a focused, hands-on introduction to research-grade network analysis in R. Designed for PhD students, faculty, and professional researchers, the workshop will cover network representations and descriptive summaries, statistical inference, stochastic block and latent-space models, community detection, link prediction, attributed network analysis, privacy-preserving data release, and reproducible R workflows for simulation, estimation, diagnostics, and visualization. Participants will gain practical skills for selecting and fitting appropriate models, evaluating assumptions, building defensible link-prediction pipelines, incorporating covariates, and translating empirical questions into reproducible analytic plans suitable for publications and grant work. The seminar is livestreamed via Zoom, with recordings, materials, datasets, code, and a monitored Q&A forum available for 30 days after the session, and participants receive an official Instats certificate of completion. #ComputationalSocialScience #DataScience #SocialTheory #Statistics #MachineLearning #PublicPolicy #Sociology #ComputerScience #R #Research #ResearchTraining #Instats

How can researchers use large language models without compromising causal rigor? Join our online seminar on Causal Inference and Large Language Models, designed for PhD students, postdoctoral researchers, and academic staff working with textual, social media, administrative, or mixed-format data. Taught by Moses Boudourides (Northwestern University), this seminar explores how LLMs can be integrated into causal inference workflows to measure latent constructs, generate candidate instruments, support causal discovery, estimate treatment effects with high-dimensional text data, and audit bias in LLM-derived variables. Participants will engage with conceptual foundations and applied workflows using reproducible, fully annotated Python and R scripts, diagnostic tools, and publication-oriented strategies. No prior knowledge of causal inference, LLMs, programming, or coding is required; general familiarity with quantitative research is sufficient. The seminar is delivered online via Zoom, with recordings, slides, scripts, data, readings, and a monitored Q&A forum available for 30 days after the seminar. Participants receive an official Instats certificate of completion, with ECTS Equivalent points where applicable. #AppliedResearch #BayesianStatistics #CausalInference #ComputationalSocialScience #ComputationalStatistics #ComputerScience #DataScience #Economics #EnvironmentalSciences #Finance #Healthcare #MachineLearning #Management #MixedMethods #OrganizationStudies #RegressionModelingStrategies #ResearchMethods #SocialSciences #Sociology #Statisticalmodellingandregression #Statistics #SocialTheory #Python #R #Research #ResearchTraining #Instats

Researchers increasingly rely on online information as empirical evidence, but turning heterogeneous web sources into reliable, analysis-ready data requires the right methodological and technical foundations. This online Instats seminar, led by Moses Boudourides of the Data Science Graduate Program at Northwestern University, offers PhD students, postdoctoral researchers, and professional researchers a rigorous, hands-on introduction to web scraping and structured data collection for academic research. Participants will learn how to identify suitable web data sources, use no-code and programmatic approaches in Python and R, parse HTML and JSON, work with APIs and dynamic content, clean and validate messy outputs, document provenance, and integrate collection workflows into reproducible research pipelines. The seminar also addresses responsible and ethical data collection, including rate limiting, terms of service, and best practices for working with human-generated content. Designed to support publishable empirical work across fields such as computational social science, finance, health sciences, and the life sciences, the seminar provides reusable scripts, templates, cleaned sample files, and documentation tools that participants can adapt directly to their own research projects. Livestream sessions are delivered via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days afterward; participants also receive an official Instats certificate of completion. #AppliedResearch #ComputationalSocialScience #DataScience #DataScraping #Finance #HealthSciences #LifeSciences #Statistics #ComputerScience #InformationScience #SoftwareEngineering #Python #R #Research #ResearchTraining #Instats

Join us for a three-day online workshop on using Large Language Models (LLMs) for qualitative social network research, taught by Professor Moses Boudourides of Northwestern University. Designed for PhD students, academic researchers, and professional researchers across anthropology, sociology, communication, media studies, organization studies, public policy, social psychology, and related fields, this hands-on seminar explores how LLMs can support qualitative coding, entity and relation extraction, socio-semantic network construction, validation, visualization, and reproducible research workflows. Participants will work in Python/Jupyter with practical notebooks and real research problems, learning how to extract actor relationships from interviews and social media, build actor–topic and actor–attribute networks, integrate outputs with NetworkX/igraph/graph-tool, assess uncertainty and bias, and document methods for peer-reviewed publications, dissertations, and grant proposals. The workshop combines methodological rigor, ethical reflection, and immediately applicable code, with live Zoom sessions, access to recordings and materials for 30 days, a monitored Q&A forum, and an official Instats certificate of completion. #Anthropology #Communication #ComputationalSocialScience #ComputerScience #Ethnography #Management #Media #OrganizationStudies #SocialMedia #SocialNetworkAnalysis #SocialPolicy #SocialPsychology #Sociology #PublicPolicy #SocialTheory #Statistics #DataScience #InformationScience #Ethics #Jupyter #Python #Research #ResearchTraining #Instats

Join us for a three-day online workshop with Professor Moses Boudourides (Data Science Graduate Program, Northwestern University) exploring how Large Language Models (LLMs) and Knowledge Graphs (KGs) can transform scholarly synthesis, systematic reviews, and theoretical discovery. Designed for PhD students, faculty, and professional researchers, this hands-on seminar series combines conceptual foundations with practical Python-based workflows delivered through reproducible Jupyter Notebooks. Across three sessions, participants will learn how to build LLM-augmented knowledge graphs, automate literature discovery, screening, and extraction, visualize theoretical landscapes, evaluate extraction quality, manage uncertainty, and design human-in-the-loop workflows that reduce hallucination risk while preserving scalability. Topics include prompt engineering, entity and relation extraction, semantic search, bibliometric and network analysis, theory mapping, provenance tracking, and responsible AI use in academic research. All sessions are livestreamed via Zoom, with recordings, slides, code, data, and a monitored Q&A forum available for 30 days after the seminar, making it easy to participate live or asynchronously. Participants receive an official Instats certificate of completion, with ECTS Equivalent points available where applicable. disciplines #ArtificialIntelligence #BibliometricResearch #ComputationalSocialScience #ComputerScience #DataScience #InformationScience #MachineLearning #Management #Multidisciplinary #SocialTheory #Linguistics #Ethics #PhilosophyofScience #CognitiveScience #Statistics #Python #Research #ResearchTraining #Instats

Join our comprehensive 5-day online workshop on Network Analysis with Python, designed for PhD students, academics, and professional researchers who want to apply network science to complex data across the natural and social sciences. Led by Professor Moses Boudourides, this hands-on seminar will guide participants through constructing and analyzing networks using Python and NetworkX, including graph types, adjacency matrices, connectivity, motifs, centrality, communities, subgraphs, paths, and network structure. Through practical coding sessions, real-world examples, discussions, and take-home skill challenges, participants will gain the tools to uncover hidden patterns, identify influential nodes, evaluate network dynamics, and apply computational network science methods to their own research. The seminar is delivered live via Zoom, with recordings, slides, code, data, and materials available for 30 days after the workshop, along with access to an instructor-monitored discussion forum. An official Instats certificate of completion is provided, with ECTS Equivalent points available for European students. #Engineering #ComputerScience #DataScience #InformationScience #Mathematics #Communication #OrganizationStudies #SocialSciences #InformationSystems #ComputationalSocialScience #SocialNetworkAnalysis #DigitalHumanities #Python #Research #ResearchTraining #Instats

Unlock new ways to model complexity with our online seminar on Hypernetworks and Hypergraphs, designed for PhD students, academics, and professional researchers working with interconnected systems. Led by Professor Moses Boudourides from the Data Science Graduate Program at Northwestern University, this four-day workshop combines theoretical foundations with hands-on Python applications to help participants analyze higher-order and multidimensional relationships that traditional network models cannot fully capture. Topics include hypergraph definitions and visualization, structural metrics, centrality, community partitioning, simplicial complexes, temporal hypergraphs, contagion models, random hypergraphs, clustering, and hyperlink prediction. With applications across computational biology, bibliometrics, chemical reaction networks, social and health network analysis, and more, the seminar equips researchers with practical tools for generating new insights into complex systems. Participants receive access to recordings and materials for 30 days, take-home skill challenges, instructor-supported discussion, and an official Instats certificate of completion, with ECTS Equivalent points available for European students. #ComputerScience #DataScience #InformationScience #ComputationalBiology #ComputationalSocialScience #SocialNetworkAnalysis #DigitalHumanities #Multidisciplinary #CognitiveScience #Biology #Statistics #Mathematics #Biostatistics #Python #Research #ResearchTraining #Instats

Ready to move from “I’d like to use text-as-data” to actually building and running your own pipeline? This three-day hands-on online seminar is designed for PhD students and professional researchers in the social sciences who want to apply text-as-data methods without getting stuck on the programming. Starting from no coding background, you’ll learn the Python you actually need, link messy datasets using spelling and semantic similarity, model themes with LDA and the Structural Topic Model, and work with BERT-based encoder models to classify political text at scale. By the end, you’ll have fine-tuned, validated, saved, and reused your own language model in free browser-based notebooks, with every step scaffolded and supported. The seminar is delivered live via Zoom in three 2.5-hour sessions, with recordings, materials, and a monitored Q&A forum available for 30 days afterward, plus an official Instats certificate of completion. #ComputationalSocialScience #PoliticalScience #ComputerScience #DataScience #Statistics #GoogleColab #Jupyter #Python #Research #ResearchTraining #Instats

Join us for a three-day online workshop, “Large Language Models and Knowledge Graphs for Scholarly Synthesis and Theoretical Discovery,” taught by Professor Moses Boudourides of the Data Science Graduate Program at Northwestern University. Designed for PhD students, faculty, and professional researchers, this hands-on seminar explores how LLMs can be integrated with Knowledge Graphs to support automated literature discovery, systematic reviews, evidence synthesis, and theory mapping across research domains. Participants will work with Python-based Jupyter Notebooks and practical workflows for KG construction, entity and relation extraction, semantic search, bibliometric and network analysis, visualization, provenance tracking, uncertainty assessment, and human-in-the-loop validation. Across three focused sessions, the workshop covers LLM-augmented Knowledge Graph construction, automated systematic review pipelines, and theory mapping for identifying conceptual relationships, clusters, and research gaps. All livestreaming sessions are delivered via Zoom, with recordings, slides, code, data, and an online Q&A forum available for 30 days after the seminar, making it easy to participate live or asynchronously. Participants receive an official Instats certificate of completion, with ECTS Equivalent points available where applicable. disciplines #ArtificialIntelligence #BibliometricResearch #ComputationalSocialScience #ComputerScience #DataScience #InformationScience #MachineLearning #Management #Multidisciplinary #SocialTheory #Linguistics #Ethics #PhilosophyofScience #CognitiveScience #Statistics #Python #Research #ResearchTraining #Instats

Abstract Generative artificial intelligence (GenAI) has field-level implications for computational communication research (CCR), not only by expanding methodological repertoires, but also by reshaping...