At Axoft

Cambridge, Massachusetts

Axoft is building the most advanced and scalable platform for implantable brain-machine interfaces. Our mission is to enable minimally invasive, long-term stable and ultra-high bandwidth communication with the brain, opening new therapies and treatments against neurological disorders and physical disabilities. We have bridged the gap between electronic and biological materials to create the softest, nanofabricated brain implants in the world. We are now looking to add talented people to the team who are passionate, deliver results, and are committed to finding creative solutions to complex problems. Axoft is looking for candidates who have demonstrated exceptional abilities and results in their previous professional, academic and interpersonal experiences and have the skillset that fits this job offer.

About the Role:

We are looking for an experienced practical minded researcher, or research minded engineer, with a strong foundation in neuroscience, computational neuroscience, or machine learning to create groundbreaking solutions in brain computer interfaces. The role focuses on leveraging insights from electrophysiology, using machine learning to undertake brain decoding.

Main Duties and Responsibilities:

Research and Development:

Utilize spike sorting, statistics and machine learning techniques, including deep learning, to analyze brain data for brain decoding.

Design and implement data analysis frameworks for brain decoding aimed at uncovering cognitive processing insights from experimental data.

Develop strategies to drive both preclinical research and clinical brain computer interface initiatives.

Assess research opportunities, identify potential applications of machine learning for neural data decoding, and integrate them into active projects.

Collaboration:

Collaborate with preclinical, clinical, software, and hardware teams to optimize data coming from brain interface process and systems.

Effectively communicate research results and findings to audiences of broad expertise both internally and externally.

Innovation:

Stay informed on advancements in brain decoding, machine learning, and related areas.

Essential Skills and Qualifications:

PhD in neuroscience, computational neuroscience, machine learning, bioengineering, computer science, mathematics, or a related discipline.

Familiar with electrophysiology data recording and analysis, with a focus on single unit brain recordings being an advantage.

Strong expertise in machine learning and statistical methods, with a proven track record of applying these to complex biological data.

Proficiency in Python, GitHub.

Capable of establishing clarity and prioritizing effectively in research settings with inherent uncertainties.

Desired Skills and Qualifications:

Previous experience in leading academic or commercial research projects.

Experience working in neurotechnology or neuromodulation of the brain.

Proficiency in C++ and application level deployment of models and data pipelines.

Knowledge of biology relevant to human cognitive processing.

A background in translating neuroscience research into commercial applications is desirable.