The inaugural annual conference hosted by TRENDS Observatory focused on societal transformations and family structures.

Research will examine how frozen lunar soil behaves in extreme conditions while providing students with hands-on opportunities in space exploration.

How can generative AI support rigorous academic research—not just produce convincing text? Join Evagoras Xydas, expert educator and CEO of IREROBOT, for a practical online seminar designed for PhD students and professional researchers. Learn to build a private, evidence-grounded research assistant using retrieval-augmented generation (RAG), Python, and locally run language models through Ollama. Working with academic literature, PDFs, qualitative data, and other research documents, you’ll explore how to retrieve relevant evidence, generate source-supported answers, and critically evaluate outputs for hallucinations, citation errors, and unsupported claims. With a focus on privacy, transparency, reproducibility, and human validation, this seminar connects practical AI skills with the standards of defensible scholarship. Attend live via Zoom or revisit the recordings and materials for 30 days after the seminar, with an expert-monitored Q&A forum available throughout that period. An official Instats certificate of completion is included. Build your AI research skills while keeping evidence and research integrity at the centre. #AppliedResearch #ArtificialIntelligence #ComputerScience #DataScience #InformationScience #Education #HuggingFace #Jupyter #Ollama #pypdf #Python #Qwen2.5 #scikit-learn #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

Great science is essential—but what makes a research proposal fundable? Join this online seminar for PhD students and professional researchers to explore how impact, collaboration, translational potential, institutional credibility and the ability to deliver at scale shape funding decisions across biomedical, health and applied research. Drawing on insights from the Australian Society for Medical Research, the seminar will help you think beyond scientific merit and position strong ideas as competitive proposals. Attend live via Zoom or revisit the recording and materials for 30 days, with access to an expert-monitored Q&A forum during that time. An official Instats certificate of completion is provided. #AppliedResearch #Biomedicine #Healthcare #HealthSciences #MedicalSciences #ResearchinHealthSciences #TranslationalResearch #PublicPolicy #Medicine #PublicHealth #Management #Education #Biostatistics #Strategy #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

What does it really mean to be “fundable” in today’s research environment? This online seminar is designed for PhD students and professional researchers working across applied research, biomedicine, healthcare, health sciences, medical sciences, and translational research who want to better understand how strong research ideas become competitive funding proposals. Scientific merit remains essential, but funding decisions increasingly also consider impact, collaboration, translational potential, institutional credibility, feasibility, scalability, and strategic alignment. Drawing on insights from the Australian Society for Medical Research, the seminar offers a valuable opportunity to explore research advocacy, funding literacy, and the wider signals that shape grant assessment today. Delivered via Zoom, the seminar can be attended live or asynchronously, with recordings, slides, materials, and a monitored Q&A forum available for 30 days after the seminar concludes. Participants receive an official Instats certificate of completion, with ECTS Equivalent points available where indicated. #AppliedResearch #Biomedicine #Healthcare #HealthSciences #MedicalSciences #ResearchinHealthSciences #TranslationalResearch #PublicPolicy #Medicine #PublicHealth #Management #Education #Biostatistics #Research #ResearchTraining #Instats

Designing a rigorous study starts with one of the most consequential decisions researchers make: sample size. This online seminar for PhD students, statisticians, data scientists, and professional researchers introduces simulation-based power analysis and sample size calculation using R, offering a flexible alternative to traditional analytical approaches that often fall short in real-world research settings. Led by Dr. Bryan Smucker from Henry Ford Health, the workshop covers classical power analysis, its limitations, and practical simulation strategies for models such as ANOVA, logistic regression, count models, and mixed-effects models. Through real examples, demonstrations, and active learning exercises, participants will learn how to build simulations that reflect their actual statistical analysis plan, evaluate tradeoffs between resources and statistical power, and communicate sample size decisions effectively with collaborators. The seminar is delivered online via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days, and participants receive an official Instats certificate of completion. #Agriculture #AppliedResearch #Bioinformatics #Biology #BiomedicalEngineering #Biomedicine #Biostatistics #Botany #ClinicalorLaboratoryScience #ClinicalResearch #CognitivePsychology #Ecology #Engineering #Epidemiology #HealthSciences #HumanFactors #LifeSciences #Medicine #Modelling #NaturalSciences #Nursing #Psychology #Psychometrics #PublicHealth #QuantitativeMethods #RegressionModelingStrategies #SocialPsychology #Statisticalmodellingandregression #Statistics #DataScience #R #Research #ResearchTraining #Instats

How can researchers move beyond rule-of-thumb regression diagnostics and make defensible, publication-ready decisions about model adequacy? This online Instats seminar, led by Ken Gerow of the Institute for Statistical and Data Science, examines common and publishable errors in assessing regression assumptions, using simple linear regression as a clear framework for understanding diagnostics that generalise across many modelling contexts. Designed for PhD students and professional researchers working with quantitative data in biostatistics, ecology, life sciences, natural sciences, statistical modelling, and related fields, the seminar focuses on key issues such as meaningful numeric variables, paired data structure, independence, model fit, goodness-of-fit interpretation, limitations of R-squared, constant variance, residual patterns, Normality of residuals, the correct order of diagnostics, joint assumption failures, model repair, and reporting for publication. Participants will gain a sharper diagnostic vocabulary and a more rigorous framework for distinguishing genuine model failure from routine variation, avoiding overclaims, and presenting regression diagnostics in a way that can withstand peer review. The seminar is delivered online via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days after the live sessions, and participants receive an official Instats certificate of completion. disciplines #AppliedResearch #Biostatistics #Ecology #LifeSciences #Modelling #NaturalSciences #Statisticalmodellingandregression #DataScience #Statistics #Research #ResearchTraining #Instats

Unlock the potential of web-derived data for rigorous, publishable research in this online seminar designed for PhD students, postdoctoral researchers, and professional academics. Led by Moses Boudourides of the Data Science Graduate Program at Northwestern University’s School of Professional Studies, this research-focused seminar introduces practical and reproducible approaches to web scraping and structured data collection across fields such as computational social science, finance, health sciences, and the life sciences. Participants will learn how to identify suitable online data sources, use no-code and programmatic extraction methods in Python and R, parse HTML, JSON, APIs, and dynamic web content, clean and validate messy outputs, document provenance, and build reproducible workflows that meet the expectations of reviewers and journals. The seminar also addresses ethical and legal considerations, rate limiting, polite scraping practices, and responsible reuse of online data. With hands-on examples, reusable templates, cleaned sample files, documentation tools, and access to recordings, materials, and a monitored Q&A forum for 30 days, participants will leave with concrete skills and artifacts they can immediately apply to their own empirical research projects. An official Instats certificate of completion is provided. #AppliedResearch #ComputationalSocialScience #DataScience #DataScraping #Finance #HealthSciences #LifeSciences #Statistics #ComputerScience #InformationScience #Python #R #Research #ResearchTraining #Instats

Join our online seminar on Web Scraping in Python for scholarly research, designed for PhD students and professional researchers who want to turn web-based information into structured, analysis-ready data. Led by Kimberly Fessel of Dr Kim Data, this practical workshop covers HTML, the DOM, browser developer tools, requests, BeautifulSoup, reproducible scraping pipelines, data cleaning, JavaScript-rendered pages, Playwright, rate limiting, robots.txt, and responsible data collection practices. Participants will learn how to extract text, links, tables, and other research-relevant content across multiple web pages, while also developing the methodological judgement needed to decide when scraping, APIs, or downloadable datasets are the best choice. Suitable for researchers across the social sciences, public health, environmental studies, digital humanities, media, and computational fields, the seminar includes Zoom livestream access, 30-day access to recordings and materials, a monitored Q&A forum, and an official Instats certificate of completion. #AppliedResearch #Biology #Business #ComputationalSocialScience #DataAnalytics #DataScience #DataScraping #DigitalHumanities #EnvironmentalSciences #Media #PoliticalScience #PublicHealth #Real-WorldData #SocialMedia #SocialSciences #Statistics #InformationScience #ComputerScience #Python #Research #ResearchTraining #Instats

Are your regression diagnostics truly publication-ready? Join Ken Gerow of the Institute for Statistical and Data Science for an online seminar designed for PhD students and professional researchers who want to move beyond rule-of-thumb interpretations and assess regression assumptions with greater confidence and methodological rigour. Using simple linear regression as a practical framework, the seminar examines common publishable errors in model diagnostics, including misuse of R-squared, weak goodness-of-fit assessment, confusion between graphical impressions and formal assumptions, residual behaviour, constant variance, independence, Normality, and the correct order of diagnostic checks. Participants will gain a clearer vocabulary for evaluating model adequacy, distinguishing genuine model failure from routine variation, repairing model problems, and reporting diagnostics in ways that can withstand peer review. This seminar is especially relevant for researchers in biostatistics, ecology, life sciences, natural sciences, statistical modelling, and other data-intensive fields. Livestream access is available via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days, plus an official certificate of completion. disciplines #AppliedResearch #Biostatistics #Ecology #LifeSciences #Modelling #NaturalSciences #Statisticalmodellingandregression #DataScience #Statistics #Research #ResearchTraining #Instats

What makes research fundable today? In a competitive funding environment, scientific merit is essential, but often not enough. This online seminar for PhD students and professional researchers explores how funding decisions across applied research, biomedicine, healthcare, health sciences, medical sciences, and translational research are increasingly shaped by expectations around impact, collaboration, translational potential, institutional credibility, feasibility, scale, and strategic alignment. Learning from the Australian Society for Medical Research, participants will gain valuable insight into national research advocacy and funding literacy, helping them better understand how to turn strong research ideas into competitive, fundable proposals. The seminar is delivered via Zoom, with recordings, slides, materials, and a monitored Q&A forum available online for 30 days after the seminar, making it easy to participate live or asynchronously. Participants also receive an official Instats certificate of completion, with ECTS Equivalent points available where shown. #AppliedResearch #Biomedicine #Healthcare #HealthSciences #MedicalSciences #ResearchinHealthSciences #TranslationalResearch #PublicPolicy #Medicine #PublicHealth #Management #Education #Biostatistics #Research #ResearchTraining #Instats

How can generative AI be used in academic research without compromising rigour, transparency, or research integrity? This online seminar for PhD students and professional researchers, led by Evagoras Xydas, expert educator, CEO of IREROBOT, and university-affiliated AI specialist, examines how to build a private, evidence-grounded research assistant using retrieval-augmented generation (RAG). Participants will learn how to prepare PDF and text collections, manage metadata, create embeddings, apply semantic search, and connect language-model outputs to a controlled evidence base for source-supported answers. The seminar also covers Python-based workflows, local open-weight models via Ollama, privacy and deployment considerations, and methods for evaluating AI outputs through source tracing, retrieval checks, faithfulness assessment, hallucination testing, and transparent reporting. Designed for researchers working with academic literature, qualitative data, policy documents, technical reports, or mixed research corpora, this practice-oriented seminar focuses not just on generating AI-assisted outputs, but on assessing whether they are defensible, reproducible, and suitable for scholarly use. Livestream access is via Zoom, with recordings, materials, and a Q&A forum available for 30 days, plus an official Instats certificate of completion. #AppliedResearch #ArtificialIntelligence #ComputerScience #DataScience #InformationScience #Education #HuggingFace #Jupyter #Ollama #pypdf #Python #Qwen2.5 #scikit-learn #Research #ResearchTraining #Instats

The Bench to Bedside series introduce important medical p...