Rate 30 Hybrid Pattern Models
Budget: £20 – £250 GBP
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.
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.