Thermodynamic Hardware Resident

What you'll do

• Design, simulate, characterize, or evaluate thermodynamic hardware and methods that exploit thermal noise and analog dynamics.
• Lead an original technical investigation and build evaluation frameworks or benchmarks for hardware and simulations.
• Co-author a research paper and present findings at the residency colloquium.

What they ask for

• Currently pursuing or recently completed an MS or PhD, or equivalent research experience, in a relevant field.
• Strong Python skills and comfort with, or eagerness to learn, C++ or Rust.
• Ability to work across device physics, circuits and architecture, algorithms, and workloads.
• Exposure to large-model inference concepts such as attention mechanisms, KV caching, or long-context decoding.

Nice to have

• Hands-on experience with simulation, experimentation, or hardware characterization, such as SPICE, PyTorch, FPGA or ASIC tooling.
• Experience writing up research or presenting technical work.

Pay

$150K

Tools

Python, C++, Rust, SPICE, PyTorch, FPGA, ASIC

AI focus

Research hardware and algorithms for AI inference using thermodynamic, stochastic analog computing; investigate how large-model inference workloads map to this hardware.