How to apply for Research Assistant

About Forecasting Research Institute

Forecasting Research Institute (FRI) is a leader in developing rigorous forecasting methods to improve decision-making under uncertainty. Their focus on empirical research and large-scale forecasting tournaments sets them apart from typical think tanks. Working here means contributing to cutting-edge research that directly informs real-world decisions.

About the role

As a part-time Research Assistant, you will support project leads in designing experiments, analyzing data, and distilling complex topics into forecastable questions. Your work will directly impact the quality of forecasting tournaments and the insights they generate. This role is ideal for someone who enjoys bridging research and practical application.

A typical day

A typical day might involve reading a research paper to extract key uncertainties, then drafting a set of forecastable questions for an upcoming tournament. You might also respond to forecaster queries via Slack or email, and later run statistical analyses on forecast accuracy data to inform experiment design.

Who Forecasting Research Institute is looking for

• Has strong research skills, including experience with literature reviews and experimental design.
• Can distill complex, technical topics into clear, testable questions (e.g., from geopolitics to AI).
• Is comfortable with data analysis (e.g., using Python, R, or Excel) and interpreting forecast data.
• Possesses excellent written communication for drafting tournament questions and responding to forecaster queries.

Tips for this application

• Tailor your resume to highlight any experience with forecasting, prediction markets, or decision science.
• Include a specific example of how you've distilled a complex topic into a clear question or hypothesis.
• Mention any familiarity with FRI's past tournaments or publications in your cover letter.
• If you have coding skills, list them explicitly and note any statistical analysis projects.
• Submit a brief writing sample that demonstrates clarity and conciseness (e.g., a short research summary).

What to cover in your cover letter

['Emphasize your ability to synthesize complex information and turn it into actionable questions.', 'Highlight any experience with experimental design, data analysis, or forecasting research.', "Express enthusiasm for improving decision-making under uncertainty and FRI's mission.", 'Show that you understand the iterative nature of refining questions based on forecaster feedback.']

Research before applying

• Review FRI's past tournament reports and published papers on forecasting methods.
• Understand the concept of 'superforecasting' and how FRI's approach differs from others.
• Familiarize yourself with the types of topics FRI covers (e.g., AI, geopolitics, pandemics).
• Look into the team structure and key researchers (e.g., Philip Tetlock, if relevant).

Likely interview topics

Based on the job description, expect questions about:

• How would you design a forecasting question about a complex geopolitical event?
• Describe a time you analyzed experimental data and what insights you drew.
• How do you handle ambiguity when a topic is unclear or lacks sufficient data?
• What is your process for conducting a literature review on an unfamiliar topic?
• How would you respond to a forecaster questioning the clarity of a tournament question?

Common mistakes to avoid

• Submitting a generic application without referencing FRI's specific work or tournaments.
• Overstating technical skills without concrete examples (e.g., 'proficient in Python' without projects).
• Ignoring the part-time nature and not indicating availability or flexibility.