micro1 is engaging Physics Experts (Statistical Physics / Quantum Information / Condensed Matter) to contribute to a research-driven customer project at the intersection of theoretical physics and numerical benchmarking.
In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Responsibilities
Analyze and provide expert insights into complex statistical physics phenomena, with a focus on replicated random-bond Ising/Ashkin-Teller models, the toric-code threshold, and the Nishimori line.
Deliver clear, well-documented solutions or critiques of problems relating to Kramers-Wannier duality, quenched disorder averaging, square-lattice self-duality, and domain-wall free energy.
Engage in advanced numerical work, particularly around 4-state Potts model simulations and interpretation.
Identify, discuss, and resolve technical challenges involving noncontractible loop defects and related topological features.
Participate as a Solver, Auditor, or Adjudicator on specific project assignments based on your experience and subfield strengths.
Preferred skills
Advanced academic background (PhD or equivalent experience) in physics, with specialization in statistical physics, quantum information, or condensed matter theory.
Direct, hands-on experience applying Kramers-Wannier duality, quenched disorder averaging, and square-lattice self-duality in research or project settings.
Demonstrated proficiency in numerical simulations involving the 4-state Potts model and analysis of domain-wall free energy.
Familiarity with topological quantum codes, particularly the toric code and its threshold phenomena.
Schedule details
5-10+ hrs/week. Fully flexible (Can accomodate after hours + weekends if needed).
Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.
Hiring companyMicro1
