Cognitive Simulation Researcher

Overview

This is a research-and-modeling role at the intersection of cognitive science, computational psychology, behavioral science and artificial intelligence. You will not summarize papers for a product team. You will decide which theories are sufficiently well supported to operationalize, convert them into explicit state variables and transition rules, define their limits, and work with engineers to test whether they produce credible behavior in THYMOS and across Aetherya’s simulations.

Your mandate

Aetherya is building persistent synthetic individuals whose behavior changes with context, history, uncertainty and social exposure. Your mandate is to make those internal dynamics scientifically defensible, computationally explicit and empirically testable.

You will own research questions from literature search through formal model, implementation specification, experiment and revision. Every mechanism should state what it represents, what evidence supports it, where it should apply, how it interacts with other mechanisms and what observation would show that it is wrong.

Core research questions

• How should hesitation, ambivalence and decision conflict evolve over time?
• How do attention, working memory, cognitive load and information order change what an agent notices or retains?
• How should prior beliefs update under new evidence, source credibility, repetition and motivated reasoning?
• How do trust, uncertainty, affect, perceived control and risk interact during consequential decisions?
• How should individual traits and accumulated experience create stable differences without reducing people to fixed stereotypes?
• Which findings replicate strongly enough to become mechanisms, priors or validation targets inside THYMOS?

What you will own

• Systematic and structured reviews of relevant cognitive and behavioral literature
• Formal definitions of latent states, observable signals, update rules, boundary conditions and competing hypotheses
• Computational models of attention, memory, belief revision, trust, persuasion, reactance, emotion and decision-making
• Research specifications engineers can implement without inventing missing scientific assumptions
• Parameter ranges and population heterogeneity grounded in empirical distributions where evidence exists
• A versioned evidence register connecting every material mechanism to sources, confidence and known limitations
• Model-ablation, sensitivity and failure-case experiments conducted with validation researchers and engineers
• Clear internal research notes and, where appropriate, publishable papers, benchmark reports or technical methods

Expected research outputs

• A concise theory map separating established effects, active debates and speculative mechanisms
• A mathematical or algorithmic specification with variables, states, transitions and pseudocode
• Testable predictions and falsification criteria before implementation begins
• Reference datasets or literature-derived target distributions where licensing permits
• An implementation review confirming that shipped behavior matches research intent
• A post-experiment decision: retain, recalibrate, constrain or reject the proposed mechanism

Required research experience

We expect graduate-level research maturity. Strong candidates will usually be current or completed master’s or PhD researchers, postdoctoral researchers, research engineers, or practitioners with an equivalent body of rigorous independent work in cognitive science, computational psychology, behavioral science, decision science, neuroscience, behavioral economics, computational social science or a closely related field.

Paid industry experience is not required. A thesis, dissertation chapter, preregistered study, replication, published or submitted paper, substantial research-assistant project, open-source model, or unusually strong independent research portfolio can demonstrate the experience we need. We care about evidence that you have taken an ambiguous question, chosen a defensible method, analyzed evidence and revised your view.

Minimum bar

• Experience independently owning at least one substantial research project from question formation to interpretation
• Ability to search, compare and critically evaluate primary literature rather than rely on narrative reviews alone
• Working knowledge of experimental design, measurement, uncertainty and common threats to validity
• Ability to express a psychological construct as an explicit, testable computational hypothesis
• Comfort distinguishing robust evidence from attractive theory, weak replication or post-hoc explanation
• Clear scientific writing and confident collaboration across research and engineering

Methods & technical profile

• Quantitative analysis in Python, R, Julia, MATLAB or an equivalent environment
• Bayesian, probabilistic, dynamical-systems, cognitive, agent-based or reinforcement-learning models
• Hierarchical models, time-series analysis, structural equation models or psychometrics
• Experiment tracking, reproducible notebooks, version control and transparent research workflows
• Experience translating papers into simulations or executable models
• LLM evaluation or multi-agent systems experience is useful, but no prompt-engineering background is required

How you will work

You will work directly with Aetherya’s founder, behavioral validation researchers and ML/simulation engineers. Research is remote and flexible, but not casual: expect a written research plan, weekly progress, documented decisions, reviewable artifacts and direct participation in model and experiment critiques.

Initial involvement is expected to average approximately 15–25 hours per week. We can accommodate a master’s or PhD program when the candidate can sustain meaningful ownership, meet agreed research milestones and handle conflicts around publication, intellectual property and institutional ethics transparently.

First six months

• Audit one existing THYMOS domain and identify unsupported assumptions, missing evidence and measurable failure modes
• Propose and specify one major mechanism, such as belief updating, trust formation, memory decay or hesitation
• Work with engineering to implement an instrumented version with visible state transitions
• Design ablations and behavioral tests that separate your mechanism from simpler alternatives
• Produce a research decision memo and external-publication plan where results warrant it
• Establish reusable standards for evidence grading and research-to-engineering handoff

How success is evaluated

• Scientific quality and traceability of mechanisms shipped into the platform
• Ability to turn ambiguous questions into bounded, falsifiable research programs
• Predictive or explanatory improvement over simpler baselines
• Reproducibility of analyses and clarity of uncertainty and limitations
• Quality and speed of collaboration with engineering and validation
• Research artifacts strong enough for expert scrutiny and selective external publication

Compensation & path to full-time

This role begins as an equity-only early-team position. Indicative grant: approximately 0.5% of Aetherya, calibrated to contribution, scope and expected long-term involvement, and subject to vesting, cliffs, company approvals and final legal documentation. No cash salary is offered during the initial part-time phase.

The role is designed to transition into a full-time research position once agreed financing or recurring-revenue milestones are reached and both sides confirm long-term fit. At transition, Aetherya intends to offer an above-market full-time cash salary for the relevant location and level. The agreed equity grant remains in place and continues under its vesting terms; it is not exchanged for salary.

Before accepting, candidates will receive written terms covering the initial scope, review milestones, expected transition conditions, vesting, intellectual property, publication and termination. Candidates should evaluate the initial equity-only period according to their own financial circumstances.

What to include when applying

• A CV or academic resume
• One or two research artifacts that show your reasoning: paper, thesis chapter, preregistration, model, analysis notebook or technical memo
• A short explanation of your personal contribution to each artifact
• A paragraph naming one cognitive mechanism you would be excited to formalize and how you might test it
• Your realistic weekly availability, program or employment constraints and earliest start date