Bridge Neurotech is building a non-invasive interface for the mind. Our aim is to image the brain's activity using ultrasound without surgery or other modifications to the body. First research study enrolling in Redwood City, California. Backed by General Catalyst.
About the role
We are looking for a PhD student in machine learning or a related field to join Bridge for a six-month internship or co-op, working on the models and infrastructure behind our neural decoding pipeline: from raw functional ultrasound acquisition through image reconstruction, preprocessing, and decoding. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking 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 a prototype to something that trains reliably on real data
- Comfort with large numerical datasets and memory-mapped arrays
- Solid grounding in first principles, for example linear algebra and signal processing
More about this role
Bridge Neurotech is building a non-invasive functional ultrasound imaging (fUSI) platform with AI-based neural decoding for brain-computer interface applications. We are a seed-stage neurotechnology company developing technology that has the potential to transform how we interact with the human brain.
We are looking for a PhD student in machine learning or a related field to join Bridge for a six-month internship or co-op, working on the models and infrastructure behind our neural decoding pipeline: from raw functional ultrasound acquisition through image reconstruction, preprocessing, and decoding.
Recent work has shown that brain activity can be mapped into the latent spaces of pretrained deep learning models to reconstruct visual perception and continuous language. This has been demonstrated with fMRI, in research settings. Our work is to bring these techniques to functional ultrasound: a modality with superior spatial and temporal resolution, portability, and a path to consumer deployment.
You will own a well-scoped project from open question to result, working closely with our ML/AI Engineering Lead.
Design, implement, train, and evaluate models for one part of the pipeline:...
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