Fellow in Human-Machine Interface Clinical Research – Bionics Lab

Harvard University; Cambridge (MA); On-site; USD 50,000 - 70,000; Full time

Job summary

Harvard University’s SEAS Bionics Lab seeks a Fellow in Human-Machine Interface Clinical Research to advance a clinical trial on muscle-driven robotic systems. The role spans neuroscience, engineering, and clinical science, offering hands-on experience with human subject research, EMG data collection, and translational work at the interface of robotics and neuroprosthetics.

Candidates will design and execute protocols, perform EMG analyses in Python or MATLAB, coordinate with clinicians and

Qualifications

• Bachelor's degree in Biomedical Engineering, Mechanical Engineering, Neural Engineering, or a closely related field.
• 2+ years of research experience, ideally involving human subjects or clinical research.
• Proficiency in electromyography (EMG) analysis and basic signal processing techniques.
• Strong programming skills in MATLAB or Python.
• Familiarity with IRB protocols, informed consent procedures, and human subject protections.

Responsibilities

• Support the design and execution of a clinical trial focused on muscle-driven robotic technologies.
• Assist in IRB protocol development and ongoing human subject documentation.
• Conduct electromyographic (EMG) recordings and signal processing to analyze motor control and performance.
• Interface with patients, clinicians, engineers, and neuroscientists as part of a collaborative team.
• Perform data collection, processing, and statistical analysis in Python or MATLAB.
• Document findings, prepare reports, and contribute to manuscript preparation.
• Ensure research activities comply with regulatory standards and ethical guidelines.

Skills

EMG analysis

Python or MATLAB programming

IRB familiarity

Human subject research

Communication skills

Education

Bachelor's degree in Biomedical Engineering, Mechanical Engineering, Neural Engineering, or closely related field

Tools

MATLAB

Python

Job description

Position

Harvard University

Title: Fellow in Human-Machine Interface Clinical Research – Bionics Lab

School: Harvard John A. Paulson School of Engineering and Applied Sciences

Department/Area: Bioengineering

Position Description

The Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) Bionics Lab is seeking a highly motivated Fellow with a background in Biomedical Engineering, Mechanical Engineering, or Neural Engineering to join our interdisciplinary research team. This position supports an exciting clinical trial exploring muscle-controlled robotic systems, pushing the boundaries of human-machine interfacing and neuroprosthetics. You will work at the intersection of neuroscience, engineering, and clinical science, gaining hand-on experience with human subject research, robotics, and electrophysiological data analysis, while contributing to impactful translational research.

Key Responsibilities

• Support the design and execution of a clinical trial focused on muscle-driven robotic technologies.
• Assist in IRB protocol development and ongoing human subject documentation.
• Conduct electromyographic (EMG) recordings and signal processing to analyze motor control and performance.
• Interface with patients, clinicians, engineers, and neuroscientists as part of a collaborative team.
• Perform data collection, processing, and statistical analysis in Python or MATLAB.
• Document findings, prepare reports, and contribute to manuscript preparation.
• Ensure research activities comply with regulatory standards and ethical guidelines.

Why Join Us?

This position offers a unique opportunity to contribute to cutting-edge research in neuroengineering, while working alongside roboticists, neuroscientists, and clinicians. You’ll gain valuable experience in clinical trial execution, device testing, and data science—skills that are highly relevant for future careers in graduate school, medical school, or industry R&D. The project is fast-paced and impact-driven, providing significant room for growth, learning, and publication.

Basic Qualifications

• Bachelor's degree (BS) in Biomedical Engineering, Mechanical Engineering, Neural Engineering, or a closely related field.
• 2+ years of research experience, ideally involving human subjects or clinical research.
• Proficiency in electromyography (EMG) analysis and basic signal processing techniques.
• Strong programming skills in MATLAB or Python.
• Familiarity with IRB protocols, informed consent procedures, and human subject protections.
• Excellent organizational skills and the ability to work independently in a fast-paced research environment.
• Strong interpersonal and written communication skills.

Additional Qualifications

• Prior experience in clinical trial operations or assisting in clinical studies.
• Familiarity with prosthetics, robotic systems, or neuromodulation technologies.
• Exposure to interdisciplinary collaboration in research settings.

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

7

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.