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MR Physicist

Nudge
San FranciscoOn-site3mo ago
Employment
Full-time

About the role

About Nudge

At Nudge, our mission is to develop the best technology for interfacing with the brain to improve people's lives. We're starting with an approach that we believe can help the most people the fastest, and also allow us to learn as much about the brain as possible: developing a non-invasive, ultrasound-based device that can stimulate and image the brain at high resolution and depth. This is a vertically integrated effort building cutting-edge hardware, software, and research capabilities to create products that can benefit millions — and eventually billions — of people.

To succeed, we need to assemble world-class teams across everything we do. We hire people who are exceptional at their craft, believe hard things are worth doing, and execute relentlessly — people who expect the highest levels of both rigor and integrity from each other.

About the role

As an MR physicist at Nudge, you will:

  • Develop novel MRI pulse sequences and image reconstruction algorithms that push the envelope of sensitivity and precision for targeting and reading out the effects of ultrasound neuromodulation

  • Build, validate, and deploy your applications on our state-of-the-art 3 Tesla Siemens Cima.X scanners

  • Own applications from concept through prototyping to deployment in clinical trials

  • Work closely with other MR physicists, an RF coil engineer, our software, mechanical, and electrical engineers, and clinical operators

About you

We are looking for MR physicists with at least 3 years of relevant post-PhD or industry experience. Regardless of career level, you should have:

  • Strong engineering / physics first principles

  • An exceptional track record of building novel MRI sequences using a major MRI vendor API, and associated image reconstruction algorithms

  • Expertise in non-Cartesian MRI pulse sequences and image reconstruction

  • Expertise in advanced MRI image reconstruction methods including parallel imaging, compressed sensing, and machine-learning

  • A degree in Electrical or Biomedical Engineering or similar engineering discipline

  • Strong signal processing and inverse problem fundamentals

  • A Demonstrated history of exceptional technical contribution

  • High integrity and strong professional judgement

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