Rate 30 Hybrid Pattern Models

I am looking for a mathematically trained researcher, PhD student, postdoc, applied mathematician, physicist, complex-systems researcher, network scientist, or computational modeller to complete a short independent classification task. The task involves classifying 30 well-known mathematical models of pattern formation and self-organisation using a supplied instruction document and Excel worksheet. Examples include reaction–diffusion models, Swift–Hohenberg, Cahn–Hilliard, Kuramoto, Ising, percolation, cellular automata, Barabási–Albert networks, Watts–Strogatz networks, lattice Boltzmann, Vicsek flocking, agent-based chemotaxis, active nematics and related hybrid models. For each model, you will identify: 1. the primary mathematical object; 2. the main operation, transformation, mechanism or interaction rule; 3. the prediction or explanatory target; 4. the approximate model category or hierarchy level; 5. whether the model is a clean fit, boundary case, hybrid, or difficult/problem case; 6. your confidence level and brief notes on any ambiguous cases. The purpose is not to write a literature review or essay. The purpose is to test whether independent mathematically trained raters classify these models in similar ways using the same structured framework. Expected time: approximately 60–120 minutes. Deliverable: completed Excel worksheet plus brief notes on ambiguous cases. Ideal background: applied mathematics, mathematical biology, nonlinear dynamics, pattern formation, statistical physics, complex systems, network science, active matter, computational modelling, agent-based modelling, or related fields. Please apply with a short note describing your relevant background and which model areas you are most comfortable with.

Project ID: 40545390