Biomedical Image Processing & Machine Learning Co-Op, (Jan - Aug 2027) - Group 02-24

The Human Health & Performance Systems Group develops human-centered technologies to overcome operational challenges and to enhance human capability in domains of interest to national security. Our research programs focus on innovative and objective solutions in the areas of integrated wearable systems, human-machine teaming, enhanced communications, neurocognitive analytics, and medical technologies. Our group is highly interdisciplinary and includes scientific experts in physiology, cognitive science, neuroscience, psychology, biomechanics, computer science, engineering, and physics. Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.

Position Description

Our team is looking for a Co-Op student with an interest in solving challenging AI/ML problems in multimodal imaging. Through this opportunity, you will work with a multidisciplinary team of engineers, including roboticists, optical designers, and electrical engineers with expertise in signal and image processing. You will prepare and process multimodal imaging datasets, develop image registration methods to align data across imaging modalities, and develop and evaluate algorithms for multimodal analysis and image fusion. The work will also explore physics-informed AI models that incorporate imaging physics into machine learning methods to improve image reconstruction and interpretation. We are looking for students who are self-motivated and interested in image processing, machine learning, deep learning, and scientific computing.

Requirements and Skills

• The candidate is a student in an M.S., or Ph.D. program in Biomedical Engineering, Electrical Engineering, Computer Science, or other relevant degree.
• Proficiency in Python and experience with standard scientific computing and machine learning libraries, and deep learning frameworks such as PyTorch or TensorFlow/Keras, through coursework or practical projects.
• Familiarity with GPU-accelerated computing using CUDA-enabled deep learning frameworks.

Preferred Qualifications

• Experience in biomedical or multimodal image processing, image registration, image fusion, or multimodal analysis.
• Interest in physics-informed AI models and incorporating physical models or constraints into machine learning methods.
• Ability to work collaboratively across disciplines and communicate technical results clearly.

Compensation:

$30-$43/hour based on education attained at the time of the co-op

Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.

MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.

Requisition ID: 43553