Neural AI Engineer — Connectomics & Neurotech

Johns Hopkins Applied Physics Lab

Laurel (MD)

On-site

USD 85,000 - 165,000

Full time

6 days ago

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Job summary

Johns Hopkins University Applied Physics Laboratory (APL) seeks a Neural Engineer to advance machine learning models, neural interfaces, and neurally-inspired AI for connectomics and neurobehavioral research.

You will join a multidisciplinary team of engineers and scientists in neuroengineering, AI, and robotics, collaborating with government and commercial partners to push the boundaries of intelligent systems while pursuing government security clearance and contributing to national

Qualifications

BS or MS in Biomedical Engineering, Computer Science, Electrical Engineering, Neuroscience, Artificial Intelligence, or related field.
Experience developing software, machine learning models, computational methods, or data analysis pipelines for scientific computing or engineering.
Experience in connectomics, neural interfaces, neurally-inspired AI, or neurobehavioral analysis.
Eligible to obtain Secret level security clearance; US citizenship required.

Responsibilities

Develop machine learning models, systems, and computational methods for connectomics, neural interfaces, neurally-inspired AI, or neurobehavioral research.
Contribute technically to a multidisciplinary neuroengineering research team with government and commercial partners.
Collaborate to develop ML algorithms, software platforms, and neurotechnology for nervous system analysis.
Communicate results through presentations, publications, reports, and demonstrations.