Statistical Modeling & Global Conflict Foresight Fellow International Truth & Trauma Institute

Statistical Modeling \& Global Conflict Foresight Fellow International Truth \& Trauma Institute (ITTI) / Outlets for Hope, Inc. **Job Type:** Fellowship / Internship **Compensation:** **Unpaid Internship / Fellowship** **Work Setting:** Remote **Start Date:** Immediate / Fall 2026 **Organization:** International Truth \& Trauma Institute (ITTI), a program of Outlets for Hope, Inc. About the Fellowship The **International Truth \& Trauma Institute (ITTI)** is seeking an exceptional, quantitatively skilled Fellow to join its research and technology team. This is an **unpaid educational fellowship/internship** designed for a highly motivated student, graduate, recent graduate, researcher, or early-career professional seeking substantive experience at the intersection of **statistical modeling, data science, conflict forecasting, political instability, collective trauma, public policy, and digital research infrastructure**. Students seeking **internship, practicum, field-placement, capstone, research, or school-required experiential hours** are encouraged to apply where permitted by their academic institution. This is **not a routine administrative internship**. The successful candidate will participate directly in the development of ITTI's emerging **Global Conflict Foresight System (GCFS™)**—a scientific forecasting architecture intended to estimate conflict and destabilization risks across multiple forecasting horizons and translate those forecasts into actionable intelligence for governments, humanitarian organizations, researchers, and corporations. The Fellow will also help maintain and develop ITTI's web-based research infrastructure, including **ITTIglobal.org** and related Observatory/dashboard environments. THE PRIMARY ASSIGNMENT: BUILDING THE GCFS™ The successful candidate will work with ITTI leadership to help transform an existing conceptual scientific architecture into a functioning quantitative forecasting system. The GCFS™ is envisioned as a forward-looking conflict probability and escalation engine incorporating ITTI's existing and emerging research frameworks, including the: * **Global Trauma Burden Index (GTBI)** * **Election Trauma Temperature Index (ETTI)** * conflict and political-violence indicators * institutional-stability measures * economic stress indicators * displacement and humanitarian indicators * governance variables * social and demographic indicators * election-cycle variables * historical conflict patterns * geospatial and event-level data * other empirically defensible predictors of instability and armed conflict The objective is not merely to describe where violence has already occurred. The Fellow will help ITTI develop models capable of asking: **What is likely to happen next, where, when, with what probability, and with what consequences?** Key Responsibilities1\. Statistical \& Predictive Modeling Assist in designing, testing, refining, and documenting statistical models capable of estimating conflict onset, escalation, persistence, and related instability. Work may include: * regression modeling * logistic/probit models * time-series analysis * panel-data models * survival/hazard models * Bayesian modeling * machine-learning approaches * ensemble forecasting * anomaly detection * classification and clustering * geospatial modeling * model calibration and validation * uncertainty estimation * sensitivity analysis * feature engineering and variable selection The Fellow should be comfortable determining **which modeling approach is scientifically appropriate**, rather than simply running predetermined analyses. 2\. Multi-Horizon Conflict Forecasting Help develop forecasting methodologies for approximately: **1-month \| 3-month \| 6-month \| 12-month \| 24-month horizons** Potential outputs include: * probability of conflict onset * probability of conflict escalation * political-violence risk * election-related instability * geographic conflict hotspots * humanitarian deterioration * institutional destabilization * displacement risk * corporate and supply-chain exposure 3\. Data Architecture \& Dataset Integration Identify, clean, structure, merge, and analyze large international datasets. Potential data sources may include conflict-event databases, governance indicators, socioeconomic datasets, election data, humanitarian statistics, population information, geospatial data, public-health datasets, institutional indicators, and other reputable international data sources. Responsibilities may include: * API-based data acquisition * dataset harmonization * missing-data management * longitudinal dataset construction * country-level and subnational data integration * automated data pipelines * reproducible analytical workflows * data-quality assessment * creation of research-ready analytical datasets 4\. Model Validation Help establish a rigorous validation framework for GCFS™. This may include: * training/testing separation * rolling-origin validation * out-of-sample forecasting * back-testing against historical conflicts * precision/recall assessment * ROC-AUC and related classification measures * Brier scores * calibration testing * false-positive/false-negative analysis * benchmark comparisons * model-drift monitoring The goal is to ensure that ITTI's forecasts are **scientifically defensible, reproducible, measurable, and continuously improvable**. 5\. Risk-Scoring Architecture Assist in translating statistical outputs into interpretable risk categories and indices suitable for policymakers, researchers, governments, humanitarian organizations, and businesses. The Fellow may help develop: * country risk scores * escalation scores * election-instability scores * trauma-vulnerability scores * geographic hotspot classifications * confidence intervals * warning thresholds * watchlists * risk trajectories * composite indices 6\. Corporate Impact \& Preparedness Modeling An important component of the project involves translating conflict forecasts into measurable organizational consequences. The Fellow may help model potential effects on: * supply chains * transportation corridors * shipping and freight * workforce safety * business continuity * market access * commodity exposure * insurance risk * infrastructure * operational costs * displacement * regulatory environments * corporate assets The long-term objective is to help transform GCFS™ forecasts into professional **Conflict Preparedness \& Enterprise Impact Reports** for organizations exposed to geopolitical and conflict-related risks. 7\. Dashboard \& Data Visualization Development Help translate complex modeling results into understandable digital outputs such as: * interactive maps * country profiles * forecasting dashboards * trend charts * risk gauges * heat maps * early-warning indicators * scenario displays * country comparisons * downloadable research outputs 8\. ITTI Website \& Digital Infrastructure **Candidates MUST have the technical ability to maintain and update a professional website such as ITTIglobal.org, or demonstrate strong transferable web-development skills.** Responsibilities may include: * maintaining website pages * updating research and Observatory content * publishing reports and datasets * troubleshooting website issues * embedding visualizations * maintaining dashboard interfaces * improving website functionality * supporting data-to-web integration * maintaining organized digital research resources This Fellowship therefore requires someone who is comfortable working across both **quantitative research and digital/web environments**. REQUIRED TECHNICAL QUALIFICATIONS Applicants **MUST possess strong statistical modeling skills**. This requirement is central to the Fellowship. Competitive candidates should demonstrate experience with several of the following: * Python * R * MATLAB * SQL * statistical analysis * predictive analytics * machine learning * time-series forecasting * regression analysis * data visualization * large-dataset management * geospatial analysis * API/data integration * web development or website administration Experience with tools or libraries such as **pandas, NumPy, scikit-learn, statsmodels, TensorFlow, PyTorch, GeoPandas, Plotly, Power BI, Tableau, or comparable analytical technologies** is valuable. Applicants do **not** need to know every technology listed above. However, applicants without substantive statistical or quantitative modeling ability are unlikely to be a good fit for this particular Fellowship. Preferred Academic Background Strong applicants may come from: * Data Science * Statistics * Applied Mathematics * Computer Science * Artificial Intelligence / Machine Learning * Economics / Econometrics * Political Science with strong quantitative training * Computational Social Science * Public Policy * International Relations with quantitative methods * Epidemiology / Biostatistics * Geographic Information Systems * Operations Research * Engineering * related quantitative disciplines Graduate students, doctoral students, advanced undergraduate students, recent graduates, and qualified early-career professionals are encouraged to apply. The Candidate We Are Looking For The ideal Fellow is someone who sees a conceptual forecasting architecture and immediately begins thinking: **What variables do we need? Where will the data come from? How should we structure the panel? What model families should we test? How do we validate the predictions? How do we quantify uncertainty? And how do we turn the results into a usable dashboard?** We are especially interested in candidates who can **build**, not merely discuss, quantitative models. Candidates should be: * intellectually curious * quantitatively rigorous * comfortable with independent research * capable of working with imperfect real-world datasets * able to document their methodology * responsive to supervision and feedback * dependa