Thermodynamic Hardware Resident

Job Title

Thermodynamic Hardware Resident

Role Summary

Join a small cohort embedded with Normal Computing's thermodynamic hardware team to perform hands-on research that spans device physics, circuits, and algorithms. The residency culminates in a co-authored research paper and a company-wide colloquium presentation.

Experience Level

Entry-level / Early career — aimed at current graduate students or recent graduates with research experience (MS or PhD level, or equivalent research experience).

Responsibilities

Work directly on experiments, simulations, and algorithm-hardware co-design to evaluate and advance thermodynamic computing.

• Design, simulate, characterize, and evaluate thermodynamic hardware where noise and analog dynamics are design elements.
• Develop numerical methods and algorithms tailored to stochastic analog substrates.
• Lead an original research investigation from scoping to execution, in partnership with staff researchers and engineers.
• Build evaluation frameworks, tests, and benchmarks for hardware and simulation results.
• Co-author a research paper and prepare results for submission with mentorship from the team.
• Present findings at the residency colloquium and communicate results to engineering and research stakeholders.
• Operate in a fast-paced startup environment, iterating quickly from idea to hardware test.

Requirements

Must-have technical skills and attributes for successful residents.

• Comfort with moving between levels of abstraction: device physics, circuit/architecture tradeoffs, and algorithms/workloads.
• Strong Python skills; willingness to use or learn a lower-level systems language such as C++ or Rust.
• Familiarity or exposure to large-model inference concepts (attention, KV caching, long-context decoding); production experience not required.
• Hands-on simulation or experimentation experience and/or hardware characterization experience (e.g., SPICE, lab measurement workflows).
• First-principles reasoning about novel computational substrates and curiosity about stochastic/analog computing.
• Strong written and verbal communication skills; ability to write and present technical research.
• Bias toward ownership and self-direction in ambiguous, fast-moving projects.

Education Requirements

Currently pursuing or recently completed a graduate degree (MS or PhD) or equivalent research experience in physics, electrical engineering, computer engineering, computer science, applied mathematics, or a related technical field.

Normal Computing is an Equal Opportunity Employer and is committed to providing reasonable accommodations. If you require assistance or an accommodation due to a disability, contact accommodations@normalcomputing.com.

About the Company

Company: Normal Computing

Headquarters: New York, NY, USA

Normal Computing develops software and hardware solutions for the semiconductor and AI infrastructure industries, specializing in ASICs for image and video diffusion inference and AI accelerators. The company focuses on architecture and microarchitecture of compute blocks, PE array design, ISA co-design, and FPGA prototyping.