ML Software Engineering Intern (PhD)

What you'll do

• Design, train, and evaluate models for reconstruction, preprocessing, or decoding; run experiments and ablations.
• Extend models and preprocessing to new data regimes, and contribute to experiment tracking, metrics, and regression checks.
• Debug numerical and performance issues, collaborate with imaging and neuroscience teams, and reproduce and present relevant research results.

What they ask for

• Currently enrolled in a PhD program in machine learning, computer science, electrical engineering, computational neuroscience, physics, or a related field.
• Available full time for six months.
• Strong Python and hands-on PyTorch development, or an equivalent framework such as JAX or TensorFlow.
• Experience taking a model from a paper or prototype to reliable training on real data.

Nice to have

• Experience with neural operators (FNO), implicit neural representations, or physics-informed machine learning architectures.
• Exposure to neural decoding, brain-computer interfaces, or neuroimaging data.

Tools

Python, PyTorch, JAX, TensorFlow, FNO

AI focus

Apply AI and machine learning to functional ultrasound imaging and neural decoding, including model development for reconstruction, preprocessing, and decoding.