PhD Research Intern, Cross-Disciplinary Vision Science

NVIDIA

. Decompose research questions into smaller, more manageable parts and tackle them in iterative steps .

Posted 10/6/2026full-timeUnited StatesEntry Level💰 $38 - $94 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Cognitive Science, Neuroscience, and Computer Science, with a strong focus on AI model training and evaluation. Proven ability to collaborate across disciplines and effectively communicate research findings through various dissemination channels.

Highest-signal resume keywords

Ph.D. CandidateProficiency In PythonExperience With AI Model TrainingKnowledge Of Cognitive ScienceFamiliarity With Deep Learning Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonRustC++AI Model TrainingQuantitative ModelingMulti-Node TrainingMulti-GPU InferenceVersion Control SystemsDeep Learning FrameworksHuman Behavior Analysis

Soft Skills

Critical ThinkingCreative Problem SolvingCollaborationCommunicationKnowledge Dissemination

Tools & Technologies

PyTorchGitGitHubGitLabTechnical Blogs

Industry Keywords

GamingHuman BehaviorResearch PublicationCross-Disciplinary ResearchIterative Problem Solving

Tech Stack

Tools & technologies

Node.jsPythonPyTorchRustC++

About the role

Key responsibilities & impact

Decompose research questions into smaller, more manageable parts and tackle them in iterative steps
Think critically to identify unseen gaps and creatively bridge them with non-traditional, high-impact solutions
Connect with researchers and product engineers to ground research findings in real-world problems
Lead knowledge dissemination efforts, with options for conference, journal, and in-house publication
Collaborate with research scientists, engineers from varied backgrounds, and product engineers on cross-disciplinary vision research

Requirements

What you’ll need

Currently pursuing a Ph.D. or equivalent academic program, demonstrated by a track record of research and publications
Deep interest in gaming and/or human behavior in related application domains
Training or systematic knowledge and skill in Cognitive Science, Neuroscience, Computer Science/Engineering, Electrical Engineering, or related fields
Proficiency with Python, Rust, and/or C++
Experience with AI model training and evaluation frameworks, like PyTorch
Experience with quantitatively modeling human perception, cognition, movement, and/or decision-making
Comfortable with modern software development and version-control systems, like git(hub/lab)
Experience with multi-node, multi-GPU training and inference workflows
Familiarity with and interest in modern deep learning models, including large-scale, multi-modal foundation models such as recent LLMs and VLMs
Demonstrated public portfolio, such as repositories, OSS contributions, notebooks, packages, or technical blog posts with code

Benefits

Comp & perks

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