Careers

Responsibilities

• Contribute to the technical specification of the system: event definition, market structure, pricing and state logic, settlement, application roles, and interface contracts — not only the subsequent code.
• Implement the event protocol: data models, market state, multiple pricing mechanisms, resolution and settlement, and the instrumentation required to record transactions, state transitions, and price indicators for later analysis.
• Build the application layer: market creation and administration, role and permission models, governance-facing views, and analysis surfaces that make event definitions, parameters, activity, and price paths interpretable.
• Integrate protocol and application over internal interfaces so definitions, trades, state changes, and prices remain consistent across components.
• Design and implement external APIs for event data, market parameters, activity, price indicators, and historical time series, including access control and integration examples for analysis and decision systems.
• Write automated tests for thin-market edge cases, settlement correctness, data integrity, and performance; support technical system tests and the first organisational pilots.
• Produce technical documentation of architecture, data models, APIs, and deployment sufficient for a research partner and for later evaluation reports.

What we expect

• Demonstrated ability to ship production-quality software across at least two of: Solidity / EVM, backend services and API design, and a typed web frontend (TypeScript / React or equivalent).
• You can read a formal specification, implement it, and push back when the spec is incomplete — including state machines, data models, and settlement or accounting logic.
• Disciplined testing, code review, and documentation. Experience with Git, automated tests, and reviewing others' work is required, not optional.
• Comfortable with market or financial primitives (order books, AMMs, scoring rules, or similar) or able to acquire them quickly from primary sources.
• Python for simulation hooks, data export, or analysis pipelines is a strong advantage. Current students may apply if they can show substantial, self-directed systems work — this is not an introductory coding role.

Appointment

From €1,017 gross per month at 12 hours/week, or from €1,271 at 15 hours/week, under the applicable collective agreement. Overpayment possible depending on classification.

Responsibilities

• Produce structured design analysis of alternative architectures and pricing mechanisms for event markets — including existing prediction-market, information-economic, and platform approaches — and document the rationale for the chosen design.
• Help specify data requirements and evaluation design before implementation: what must be logged, which parameters vary, which baselines are used, and which claims the experiments can and cannot support.
• Build and extend Python simulations and experimental scenarios: participant count, information structure, trading frequency, starting liquidity, and strategic behaviour, including thin-market failure modes.
• Evaluate implemented mechanisms on signal availability, response to new information, stability under large trades, calibration on resolved events, cost of liquidity, and the influence of individual participants. Report results by market size; do not average away the research question.
• Define and review data models so protocol and API output are actually analysable: event parameters, market state, transactions, price paths, and usage data.
• Specify and, where appropriate, implement analysis and visualisation for price paths, cross-market comparison, and time-series export — and flag when a display would invite a false interpretation.
• Plan and document technical tests and organisational pilots with the project lead and the Complexity Science Hub; contribute the empirical sections of the evaluation reports.

What we expect

• A current or very recent degree in computer science, mathematics, statistics, physics, economics, or a closely related field, with evidence of independent quantitative work — a thesis, a paper, a model, or a substantial repository you can walk through.
• Fluent in Python for modelling, simulation, and careful data work. You write code that another researcher can rerun.
• Able to read technical and scientific literature and turn it into precise notes, testable claims, and written argument. Mechanism design, market microstructure, or prediction markets is a strong advantage; willingness to work from primary sources is required.
• You are comfortable saying when a metric is invalid (for example, ex-post forecast scores on unresolved events) and when a result is an artefact of averaging across market sizes.
• This is not a role for first exposure to programming or to data analysis. If your strongest evidence is coursework alone, this appointment is not the right fit.

Appointment

From €763 gross per month at 18 hours/week, or from €848 at 20 hours/week, under the applicable collective agreement. Overpayment possible depending on classification.