Summer 2027
Ph.D. Research Graphics and Simulation Intern
Graphics and Simulation
Posted on 8/19/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$38 - $94/hr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
PhD
 AI & Machine Learning (1) |
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- Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field for the full duration of the internship.
- The anticipated graduation date, including month and year, must be clearly indicated on a resume or curriculum vitae.
- Depending on the internship, experience or knowledge may include Python, C, CUDA, HLSL or GLSL, and machine learning frameworks such as PyTorch, JAX, or Warp.
- A strong background in research with publications at top conferences is required.
- Research experience in at least one potential internship area is required, including real-time graphics and rendering; differentiable rendering; ray tracing and path tracing; neural rendering models; light transport and material or shape modeling; physics-based simulation; world models; deep learning for animation; three-dimensional and four-dimensional content creation; virtual and augmented reality environments; generative artificial intelligence for graphics, simulation, and content creation; three-dimensional deep learning; digital human creation; human motion modeling; GPU-accelerated algorithms and systems for graphics and simulation; or synthetic data generation.
- Design and develop algorithms, hardware, and software that advance computing, graphics, media processing, and other technologies central to NVIDIA’s business.
- Invent new techniques, technologies, methodologies, processes, and devices to enable new products or types of products.
- Deliver prototype results, patents, products, and publications as applicable.
- Collaborate with team members, other teams, and external researchers.
- Experience with large-scale model training is a plus.
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
Get referred to NVIDIA
See people who can refer or advise you
Simplify's Take
What believers are saying
- Q2 FY2026 revenue reached $46.7 billion, up 56% year over year.
- OpenAI's Ohio campus could generate $150 billion to $200 billion for NVIDIA.
- NVIDIA's $1.5 billion SB Energy deal secures 8 gigawatts of future demand.
What critics are saying
- China blocked H200 shipments in January 2026, cutting a major revenue lane immediately.
- NVIDIA's $105 billion Ohio backstop ties capital to OpenAI lease risk through 2032.
- Google, AWS, and AMD are racing to compress NVIDIA's pricing power by 2027.
What makes NVIDIA unique
- Blackwell Data Center revenue grew 17% sequentially in Q2 FY2026.
- Networking revenue hit $7.3 billion, proving NVIDIA sells full AI systems.
- NVIDIA controls scarce compute, power, and software across training, inference, and networking.
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Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -2%2 year growth
↓ -3%Investment strategist Louis Navellier has set a $300 price target for Nvidia stock by year-end, requiring just 37% appreciation from its current $219 level. He argues this target is conservative given the company's forecast 88.7% earnings growth for fiscal 2027. Nvidia posted 85% revenue growth and 140% earnings growth year-over-year in its first quarter. Second-quarter results, due 26 August, are expected to show 96.5% revenue growth to $91.85 billion and 98.1% earnings growth to $2.08 per share. For fiscal 2027, revenue is forecast to reach $393.85 billion, up 82.4% year-over-year, with earnings projected at $9 per share. Applying Nvidia's current price-to-earnings ratio of 34 to these earnings yields a $306 target. Navellier also highlighted Ciena Corporation as a strong AI infrastructure play, noting third-quarter earnings estimates have risen 9% recently.
Stifel analyst Ruben Roy has reiterated a Buy rating on Nvidia with a $282 price target ahead of its 26 August earnings report. The bullish stance is backed by supply chain signals from key partners Foxconn and Super Micro Computer. Foxconn reported second-quarter revenue of NT$2.53 trillion, up 41% year-on-year, with its cloud and networking segment exceeding 50% of revenue for the first time. The company expects full-year AI rack shipments to more than double. Super Micro reported $11.1 billion in fourth-quarter revenue, nearly double from a year earlier, and booked over $60 billion in new orders in a single quarter. The company guided first-quarter sales between $14.5 billion and $15.5 billion, well above analyst expectations of $11.9 billion. Both companies' results point to accelerating AI infrastructure demand, supporting Stifel's expectation that Nvidia will beat estimates and raise guidance.
Google has struck a major custom-chip deal with Marvell covering AI inference accelerators and silicon supporting Google's TPU ecosystem. The agreement includes warrants for Google to purchase up to 58.97 million Marvell shares at $206.58 each, potentially worth roughly $12.18 billion. The move intensifies competition in AI hardware as hyperscalers build alternatives to Nvidia's dominant GPUs. Custom silicon doesn't need to destroy Nvidia's position—it only needs to capture a larger share of inference spending. Despite the competitive pressure, Nvidia reported first-quarter revenue surged 85% to a record $81.6 billion, with its Data Centre segment jumping 92% to $75.2 billion. The company maintains a GF Score of 95 out of 100, reflecting strong profitability and growth. Whilst Nvidia retains its leadership position, the AI chip market is becoming increasingly crowded as tech giants invest in specialised alternatives.
Nvidia is connecting companies with its GPUs to data-centre operators with available capacity in the Nordics, sources told CNBC. The move reflects the chip giant's efforts to expand its influence across the AI ecosystem beyond semiconductors. Two sources said Nvidia has offered to introduce firms with data centres in the region to companies with its GPUs seeking capacity. The approach is part of what Nvidia sees as its "value proposition to GPU customers", one source said. The Nordics are attracting large AI data-centre projects due to access to power and land, plus cooler climates that aid cooling. Pure DC said in July it would invest €1.5 billion to build a 110 MW campus in Finland. In April, Microsoft announced it would take up extra capacity at an Nscale site in Norway.
Investor Michael Burry has identified chip startup Etched as serious competition for Nvidia. The company, founded in 2022 by three 24-year-old Harvard dropouts, recently raised $700 million in a funding round led by Jane Street, valuing it at $21 billion. Etched has now raised nearly $2 billion total. The startup focuses on AI inference chips and claims it took just 44 days to run inference workloads after receiving test chips from Taiwan Semiconductor Manufacturing, a process typically taking six months or more. Roughly 15% of Etched's 400 employees previously worked at Nvidia, including 23-year veteran Brian Loiler. Burry, known for his bearish stance on Nvidia, highlighted Etched's rapid development in a post on X, citing a Wall Street Journal report on the startup's progress.