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Neural Interface Engineer Jobs in Chicago, IL (NOW HIRING)

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Neural Interface Engineer information

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$11.3K

$109.6K

$218.9K

How much do neural interface engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for neural interface engineer in Chicago, IL is $109,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,200.00 and $211,200.00 per year, depending on experience, location, and employer.

What is the difference between Neural Interface Engineer vs Brain-Computer Interface Developer?

AspectNeural Interface EngineerBrain-Computer Interface Developer
Required CredentialsBachelor's or Master's in Neuroscience, Biomedical Engineering, or related fieldsBachelor's or Master's in Computer Science, Neuroscience, or Biomedical Engineering
Work EnvironmentResearch labs, medical device companies, biotech firmsTech startups, research institutions, healthcare companies
Industry UsageDevelops hardware/software for neural data acquisition and processingDesigns algorithms and interfaces for translating neural signals into commands
Common Search/ComparisonOften compared due to overlapping skills in neural data and hardware developmentRelated but more software-focused

Neural Interface Engineers focus on developing hardware and systems to connect the nervous system with external devices, while Brain-Computer Interface Developers primarily design software algorithms to interpret neural signals. Both roles require knowledge of neuroscience and engineering, but differ in their emphasis on hardware versus software development.

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Neural Interface Engineer jobs near you
Postdoctoral Appointee - Experimental AI

Postdoctoral Appointee - Experimental AI

Argonne National Laboratory

Lemont, IL • On-site

$49K - $67K/yr

Full-time

Posted 24 days ago

Job description

Job Summary:
Argonne National Laboratory is dedicated to scientific discovery and innovation, and they are seeking a Postdoctoral Appointee for research in experimental AI applications. The role involves computational and experimental work aimed at developing AI and automation tools for electrochemical research.
Responsibilities:
• developing and implementing experimental focused application of AI and automation tools for unraveling fundamental interfacial processes in materials for electrochemistry
• involve some experimental work in adapting workflows for automation and artificial intelligence optimization schemes
• developing AI models to uncover structure-function relationships with limited data sets
• building automated electrode-electrolyte interface discovery workflows
• implementing full autonomous experimental campaigns
• learning experimental workflows and adapting them for autonomous control
Qualifications:
Required:
• Ph.D. completed in the past 5 years or soon-to-be completed in chemistry, chemical engineering, materials science, or a closely related field
• Strong background in fundamental electrochemistry
• Well versed in code development
• Application of AI model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships
• Familiar with optimization approaches such as genetic search, Bayesian optimization
• Ability to think and work independently
• Conduct research in a highly interdisciplinary environment of chemists, physicists, and materials scientists
• Good communication skills and fluent in both spoken and written English
• Demonstrate evidence of initiative and problem-solving in research projects
Preferred:
• Hands-on expertise in computational materials science
• Familiarity with electrochemical instrumentation suite (potentiostat, cyclers, electronic load) and materials characterization
Company:
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management. Founded in 1946, the company is headquartered in Lemont, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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