Neurophysiology Scientist I - In Vivo Electrophysiology

Allen Cell; Seattle (WA); Hybrid; USD 87,000 - 108,000; Full time

Benefits offered by this job

Relocation assistance

Possible visa sponsorship

Job summary

The Allen Institute's Global Brain Observatory seeks a Scientist I to advance electrophysiological recordings and behavioral training across neuroscience topics such as reward learning, predictive processing, and cognition. The ideal candidate brings strong engineering skills, a PhD in a relevant field, and a collaborative approach to research.

The role is onsite with limited remote work, offering relocation assistance and potential visa sponsorship.

Qualifications

• PhD in neuroscience, biological sciences, biomedical engineering, or an equivalent combination of education and experience.
• 2–3 years of experience in in vivo electrophysiology.
• Strong fundamentals in physics and engineering.
• Experience with in vivo recordings using fiber photometry.
• Experience training rodents in behavioral tasks.
• Exposure to and handling of laboratory animals.

Responsibilities

• Pilot and conduct in vivo electrophysiological experiments using Neuropixels probes.
• Collect, process, and analyze neurophysiological and behavioral data.
• Maintain detailed experimental protocols and documentation.
• Troubleshoot technical issues with electrophysiology equipment and recording systems.
• Contribute to manuscript preparation and presentation of findings at scientific conferences.
• Mentor junior research staff on experimental techniques.
• Collaborate with other internal and external teams on interdisciplinary projects.
• Participate in lab meetings and scientific discussions.

Skills

In vivo electrophysiology

Data analysis

Neuroscience concepts

Education

PhD in neuroscience or related field

Tools

Neuropixels probes

Fiber photometry

Job description

The Allen Institute's Global Brain Observatory seeks a Scientist I to advance electrophysiological recordings and behavioral training across neuroscience topics such as reward learning, predictive processing, and cognition. The ideal candidate brings strong engineering skills, a PhD in a relevant field, and a collaborative approach to research.

The role is onsite with limited remote work, offering relocation assistance and potential visa sponsorship.