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Neural Interface Research Jobs (NOW HIRING)

Neuralink

Machine Learning Engineer

Austin, TX

You will have access to the most cutting-edge neural interface hardware and develop ... Formulate research questions to guide the development of neural networks and signal processing ...

Delsys

R&D Software Engineer (FT)

Natick, MA · On-site

$90K - $110K/yr

... neural interface technologies. The position requires expertise in developing signal processing and ... Successful candidates will collaborate closely with developers, R&D engineers and scientists ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

You will have access to the most cutting-edge neural interface hardware and develop ... Formulate research questions to guide the development of neural networks and signal processing ...

Neara

R&D Senior Process Engineer

Addison, TX · On-site

$100K - $130K/yr

We are seeking a R&D Senior Process Engineer to lead the materials and MEMS manufacturing development of our neural interface technologies. This role owns the development of our thin-film based ...

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Neural Interface Research information

What is neural interface research?

Neural interface research is the scientific study and development of technologies that connect the nervous system, particularly the brain, with external devices or computers. These interfaces, often called brain-computer interfaces (BCIs) or neural prosthetics, enable direct communication between neural tissue and electronic systems. The goal of this research is to restore lost sensory or motor functions, treat neurological disorders, or enhance human capabilities. Neural interface research is highly interdisciplinary, involving neuroscience, engineering, computer science, and medicine. Advances in this field have the potential to revolutionize healthcare and human-machine interaction.

What are the key skills and qualifications needed to thrive in neural interface research?

To thrive in Neural Interface Research, you need advanced knowledge in neuroscience, biomedical engineering, and signal processing, often supported by a graduate degree in a related field. Proficiency with programming languages (such as Python or MATLAB), neural data acquisition systems, and simulation tools is typically required. Exceptional problem-solving abilities, collaboration, and strong communication skills help researchers innovate and translate findings across multidisciplinary teams. These skills are crucial for developing cutting-edge neural technologies and ensuring rigorous, impactful scientific progress.

What are some common interdisciplinary challenges faced by professionals in neural interface research teams?

Neural Interface Research teams often bring together experts from neuroscience, engineering, computer science, and clinical backgrounds, which can lead to challenges in communication and aligning goals across disciplines. Collaborators may use different terminology or have varying expectations regarding project timelines and outcomes. Successful professionals in this field need to be proactive in fostering clear communication, demonstrating adaptability, and developing a basic understanding of adjacent fields to effectively contribute to collaborative projects. These interdisciplinary challenges ultimately offer valuable opportunities for personal growth and innovation.

What is the difference between Neural Interface Research vs Neural Engineering?

AspectNeural Interface ResearchNeural Engineering
Required CredentialsAdvanced degrees in neuroscience, biomedical engineering, or related fieldsSimilar credentials, often with additional focus on device design and implementation
Work EnvironmentResearch labs, universities, biotech companiesResearch labs, medical device companies, clinical settings
Industry UsageFocuses on developing and understanding neural interfacesDesigning, testing, and applying neural interface devices
Common Search IntentResearch methods, latest advancements, academic rolesProduct development, device engineering, clinical applications

Neural Interface Research primarily involves exploring and understanding neural interfaces through scientific investigation, while Neural Engineering focuses on designing and developing neural interface devices for practical use. Both roles require similar educational backgrounds but differ in their application and work environment.

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Infographic showing various Neural Interface Research job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 88% Full Time, 9% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Fellow in Biohybrid Systems & Neural Interfaces - Harvard Bionics Lab

Cambridge, MA • On-site

Harvard University
Colleges, Universities, and Professional Schools • 51 - 200 employees
Learn more about Harvard Universityexternal

$50K - $70K/yr

Full-time

Re-posted 29 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

83rd of 633 rated colleges and universities

Job description

Position
Details
Title
Fellow in Biohybrid Systems & Neural Interfaces - Harvard Bionics Lab
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Bioengineering
Position Description
The Harvard Bionics Lab is seeking a Fellow to support experimental and translational research at the interface of neural engineering, bioelectronics, and physiology. The role focuses on developing and evaluating sensing technologies for peripheral nerve and organ interfacing, with an emphasis on in vivo rodent (rat/mouse) models.
The Fellow will work closely with a multidisciplinary team to design, build, and test sensor systems for recording neural and physiological signals. Responsibilities include conducting survival surgeries in rodents, performing electrophysiological recordings, developing and prototyping sensing hardware, and executing structured data collection protocols.
The candidate will contribute to experiments involving nerve interfacing, signal acquisition, and biomarker-driven systems. This includes working with peripheral nerves, muscles, and/or organ systems to quantify physiological responses and neural activity. The role will also involve analyzing datasets, maintaining rigorous experimental documentation, and supporting iterative device development.
A significant portion of the work will require hands-on experimentation, including rodent handling, surgical procedures, and electrophysiology. The candidate is expected to operate independently within defined protocols and contribute to troubleshooting and optimization of experimental systems.
Basic Qualifications
  • Bachelor's or Master's degree in Bioengineering, Biomedical Engineering, Neuroscience, Physiology, or Electrical Engineering
  • Prior hands-on experience with rat or mouse models (required)

Additional Qualifications
  • At least 1-2 years of research experience in an academic or industry lab setting
  • Experience with electrophysiology (neural recording, EMG, or related techniques)
  • Exposure to sensor design, bioinstrumentation, or embedded systems
  • Programming experience (e.g., MATLAB, Python, or similar for data acquisition/analysis)
  • Familiarity with surgical techniques or willingness to be trained in rodent survival surgeries
  • Strong organizational skills and attention to experimental rigor and reproducibility

Special Instructions
  • Candidates must be available for a full-time, 12-month commitment
  • Applications should include a CV and brief statement of research experience
  • At least two references required

Contact Information
Allison Choat
Contact Email
achoat@g.harvard.edu
Salary Range
$50,000 - $70,000
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required
2
Maximum Number of References Allowed
3
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