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Based on 240 similar postings.
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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
896 open roles
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Listed pay typically runs
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NVIDIA 2027 Internships: Ph.D. Research Hardware is a research-focused role within the hardware team designed for students currently pursuing a Ph.D. in Computer Science, Electrical Engineering, or related fields. The successful candidate will design and implement novel approaches to circuit and VLSI design, including ASIC development and advanced EDA methodologies. Day-to-day responsibilities involve collaborating with internal teams and external researchers to transfer research into products, resulting in prototypes, patents, or published original research. Required technical skills include Python, C, C++, Perl, MATLAB, CUDA, Verilog, SystemVerilog, CAD tool packages like Cadence or Synopsys, HFSS, and PyTorch. Relevant domain expertise may include circuit design, SerDes, integrated photonics, memory design, power delivery, security circuits, high-speed logical design, ML accelerators, hardware/software co-design, and electronic design automation for GPU accelerated EDA.
Design and implement novel approaches to circuit and VLSI design.
Develop ASIC designs and advanced EDA methodologies.
Translate research findings into practical products for internal product groups.
Produce tangible deliverables including prototypes, patents, and published original research.
Conduct research in specialized areas like high-speed signaling, memory design, or ML accelerators.
Utilize hardware description languages such as Verilog and SystemVerilog for circuit development.
Develop software solutions using Python, C++, CUDA, or machine learning frameworks.
What we're looking for
Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field.
Must provide an anticipated graduation date on the resume or CV for consideration.
Strong background in research with publications at top conferences and/or patents.
Experience with programming languages and tools such as Python, C, C++, Perl, MATLAB, CUDA, Verilog, SystemVerilog, and ML Frameworks like PyTorch (preferred).
Experience with CAD tool packages or EDA tools (preferred).
Research experience in specific areas such as Circuit Design, SerDes, Memory Design, Power Delivery, Security Circuits, or ML Accelerators (preferred).
CUDA
C++
C
Python
GPU Architecture
CPU Architecture
Operating Systems
Distributed Systems
AI
Parallel Computing
Compilers
VLSI
EDA
High-Performance Networking
Hardware-Software Co-design
LLM Training
Memory Systems
CUDA
C++
C
Python
GPU Architecture
CPU Architecture
Operating Systems
Distributed Systems
AI/ML Systems
LLM Training
VLSI
EDA
Parallel Computing
High-Performance Networking
Hardware-Software Co-design
Memory Systems
Multi-GPU Architecture
Python
C++
CUDA
PyTorch
JAX
TensorFlow
MuJoCo
Deep Learning
Robotic Manipulation
Motion Planning
Reinforcement Learning
Sim-to-Real
Foundation Models
Robot Kinematics
Dynamics
Synthetic Data Generation
Python
C++
CUDA
PyTorch
TensorFlow
Deep Learning
Large-scale Model Training
LLMs
Multimodal Models
Sensor Fusion
Digital Twins
Simulation
Model Distillation
Inference Optimization
Control Barrier Functions
Computer Vision
Deep Learning
Python
C++
CUDA
PyTorch
TensorFlow
3D Vision
Scene Understanding
Neural Rendering
Diffusion Models
NeRFs
Vision Transformers
Neural Architecture Search
Synthetic Data Generation