PhD Research Intern, Cross-Disciplinary Vision Science

What you'll do

• Decompose complex research questions into smaller, manageable parts for iterative problem-solving.
• Identify unseen research gaps and develop non-traditional, high-impact solutions.
• Collaborate with researchers and product engineers to ground findings in real-world problems.
• Lead knowledge dissemination efforts through conference, journal, and in-house publications.
• Train and evaluate AI models using frameworks like PyTorch.
• Quantitatively model human perception, cognition, movement, and decision-making.
• Manage multi-node, multi-GPU training and inference workflows for large-scale foundation models.

What we're looking for

• Currently pursuing a Ph.D. or equivalent academic program with a track record of research and publications.
• Training or systematic knowledge 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 (preferred).
• Comfortable with modern software development and version-control systems like git (preferred).
• Experience with multi-node, multi-GPU training and inference workflows (preferred).
• Familiarity with and interest in modern deep learning models, including large-scale, multi-modal foundation models (preferred).