PhD Research Intern, Electronic Design Automation - 2027

NVIDIA
Santa Clara
Workplace: OnsiteInternshipUSD 38 - 94 hourlyFunction: Research & Scientific (R&D)Education: phdSkills: ["Self-motivation","Creativity","Collaboration","Written communication","Verbal communication"]

Work on research that applies agentic AI, LLMs, and GPU acceleration to chip design workflows. You’ll develop and test innovative EDA algorithms and software, collaborate with circuit, VLSI, and architecture teams, and aim to publish and present original research. The role spans areas such as GPU-accelerated optimization, physical design, formal methods, reinforcement learning, and research-driven prototyping using tools like Python and C++.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

PhD Research Intern, Electronic Design Automation - 2027

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Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Work on research that applies agentic AI, LLMs, and GPU acceleration to chip design workflows. You’ll develop and test innovative EDA algorithms and software, collaborate with circuit, VLSI, and architecture teams, and aim to publish and present original research. The role spans areas such as GPU-accelerated optimization, physical design, formal methods, reinforcement learning, and research-driven prototyping using tools like Python and C++.
Location: Santa Clara
Workplace: Onsite
Employment Type: Internship
Job Function: Research & Scientific (R&D)
Seniority: Intern level

Key Responsibilities

  • •Apply agentic AI, LLMs, generative AI, reinforcement learning, and GPU acceleration to chip design workflows.
  • •Research and develop innovative EDA software and algorithms.
  • •Collaborate with circuits, VLSI, and architecture team members across research and product teams.
  • •Plan to publish and present original research.
  • •Drive groundbreaking research at the intersection of AI, GPU computing, formal methods, and EDA.

Pay and Benefits

Salary: USD 38 - 94 hourly

Key Requirements

  • •Pursuing a PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
  • •Publications in leading EDA or AI conferences on AI for EDA, formal methods, or GPU-accelerated EDA.
  • •Excellent programming skills in rapid prototyping environments such as Python; C++ and parallel programming (e.g., CUDA) are a plus.
  • •Expertise in EDA (e.g., formal verification, logic synthesis, physical design, timing and signoff) algorithms, with publications/project experience applying AI to impactful problems.
  • •Excellent self-motivation, creativity, passion for research, collaboration skills, and the ability to work effectively in a research team.
Experience:AIGPU computingEDAFormal methodsResearchChip design
Education:PhD / Doctorate in Electrical Engineering, Computer Engineering, Computer Science, or related fields
Skills:Self-motivationCreativityCollaborationWritten communicationVerbal communication
Tech Stack:AIGPU computingPythonC++CUDALLMsAgentic AIGenerative AIReinforcement learningElectronic Design Automation (EDA)Formal verificationLogic synthesisPhysical designVLSITiming and signoff

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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