AI-Driven Seizure Research Fellow (Two-Photon Imaging)

Oslo University Hospital; Oslo; On-site; NOK 700,000 - 900,000; Full time

Benefits offered by this job

Salary in accordance with collective =

Pension and insurance

Professional development opportunities

Job summary

Oslo University Hospital, Department of Neurology, and GliaLab at the University of Oslo, invite applications for a Researcher or PhD fellow to work on AI-driven closed-loop optogenetic seizure control. The role involves in vivo mouse imaging, electrophysiology, and machine-learning based seizure detection, based at GliaLab in Oslo.

The successful candidate will join a multidisciplinary team and contribute to cutting-edge neural imaging and AI methods, with strong emphasis on collaboration and

Qualifications

• Completed Master’s degree (or equivalent) in neuroscience, medicine, biology, biomedicine, or a related field.
• Documented experience with in vivo rodent experimental work.
• FELASA-equivalent certification in laboratory animal science (or willingness to obtain this) is required; prior hands-on animal experience prioritized.
• Track record of first-author publication(s) in the field.
• Ability to co-supervise PhD/master students and contribute to project leadership.
• Fluent oral and written communication skills in English.

Skills

Fluent English

Problem solving

Independent work

Team collaboration

Programming (Python/MATLAB)

Machine learning knowledge

Statistics knowledge

Communication skills

Teaching abilities

Education

Master's degree in neuroscience/biomedicine/related field

PhD in neuroscience or related field

Tools

Two-photon microscopy

Neuropixels

EEG telemetry

Job description

Oslo University Hospital, Department of Neurology, and GliaLab at the University of Oslo, invite applications for a Researcher or PhD fellow to work on AI-driven closed-loop optogenetic seizure control. The role involves in vivo mouse imaging, electrophysiology, and machine-learning based seizure detection, based at GliaLab in Oslo.

The successful candidate will join a multidisciplinary team and contribute to cutting-edge neural imaging and AI methods, with strong emphasis on collaboration and