Postdoctoral Research Fellowship: Network Thermodynamics of Distributed Computation

Collaborate with PI and other team members to advance this project through research, publication, workshop organization, etc.

Develop and apply mismatch-cost theory and large-state-space approximation techniques (e.g., coarse-graining, uncertainty quantification, backward differential equations tensor networks, Monte Carlo) to distributed computational systems

Design, train, and analyze distributed computational systems — such as feedforward neural networks, restricted Boltzmann machines, and lightweight LLMs — to relate their network topology to thermodynamic cost, robustness, and speed, and computational power.

Investigate how the "hardness" of computational problems (e.g., KSAT) relates to the thermodynamic cost of solving them.

Ph.D. in Physics, Computer Science, or a related field (by start date).

Background in stochastic thermodynamics, statistical physics, or theoretical computer science (computational complexity).

Familiarity with Monte Carlo methods, uncertainty quantification, backward differential equations, and/or tensor network approximations.

Strong programming skills and interest in interdisciplinary collaboration spanning physics and computer science theory.

Please upload a current and complete CV and a 1-page research statement. Please request that three academic Letters of Recommendation be sent directly to ariel@santafe.edu (Ariel Dooner, HR Manager).

SFI is an Equal Opportunity Employer and is committed to fostering a diverse and inclusive academic global community. Women and members of underrepresented groups are especially encouraged to apply. U.S. citizenship is not a requirement, however, you must be legally able to work in the US. SFI will sponsor a J1 Visa for successful candidates. SFI is not able to sponsor a H1B Visa for candidates.