At Dartmouth's Cluster for Improving Healthcare Outcomes through Sensory Technology
Description
The Cluster for Improving Healthcare Outcomes through Sensory Technology at Dartmouth invites applications for a Postdoctoral Researcher with expertise in systems integration, embedded machine learning, and human-subject research for wearable health technologies.
We seek a hands-on systems researcher who can bridge hardware, firmware, and ML to build end-to-end wearable sensing platforms. The postdoc will lead the integration of multi-modal sensing systems, develop and deploy on-device ML algorithms, and coordinate human-subject evaluations from IRB preparation through data collection and analysis.
This position is full-time, non-remote, and in-residence at Dartmouth in Hanover, NH, with a start date as early as Spring 2026. The postdoc will be hosted in Computer Science and supported by the Guarini School for Graduate and Advanced Studies.
Key Responsibilities
- Lead end-to-end system integration of wearable sensing platforms, connecting hardware, firmware, mobile apps, and cloud infrastructure.
- Develop and optimize embedded ML algorithms for on-device inference on resource-constrained wearable platforms.
- Build data acquisition pipelines, real-time signal processing workflows, and lightweight dashboards for research and clinical teams.
- Design, submit, and manage IRB protocols for human-subject studies; coordinate participant recruitment and data collection.
- Conduct human-subject evaluations including study design, device deployment, and systematic data analysis.
- Collaborate with hardware engineers to integrate sensors, validate signal quality, and troubleshoot system-level issues.
- Implement model compression, quantization, and efficient inference techniques for edge deployment (TFLite, ONNX, etc.).
- Maintain version control, documentation, and reproducibility across hardware, firmware, and ML components.
- Prepare publications, figures, datasets, and technical reports; contribute to grant proposals and tech-transfer activities.
- Mentor graduate and undergraduate students on systems research and human-subject study practices.
Required Qualifications
- Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or related field by start date.
- Demonstrated experience building and integrating wearable or embedded sensing systems from prototype to deployment.
- Strong programming skills in Python and C/C++; experience with embedded platforms and mobile development.
- Hands-on experience developing and deploying ML models for time-series biosignal data.
- Track record of conducting human-subject research including IRB protocol preparation and study execution.
- First-author publications or documented delivery of integrated sensing systems with ML components.
Additional Experience That Will Strengthen the Application
- Experience with embedded ML frameworks (TensorFlow Lite, ONNX Runtime, Edge Impulse) and model optimization techniques.
- Familiarity with wearable hardware integration: sensor interfaces, power management, BLE communication.
- Background in clinical research coordination, multi-site studies, or regulatory considerations for digital health.
- Experience with data governance, secure data pipelines, and compliance requirements for human/biological data.
- Knowledge of real-time systems, closed-loop control, or adaptive interventions.
Application Instructions
Submit via email to cihost@dartmouth.edu with subject line "CS Postdoc Application [Your Name]":
- Cover Letter describing your systems integration experience, ML background, and human-subject research experience
- CV with publications and links to relevant projects, code repositories, or demos
- Two representative publications demonstrating systems work or ML for health applications
Review of applications will begin immediately and continue until the position is filled. For inquiries, contact Professor Tam Vu, Cluster Head, at Tam.N.Vu@dartmouth.edu.
Equal Employment Opportunity Statement
Dartmouth College is an equal opportunity employer under federal law. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications are welcome from all.
Dartmouth is committed to accessibility for its community. If you are an applicant with a disability and would like to request a reasonable accommodation, please email ADA@Dartmouth.edu with the subject line "application accommodations."
Applicants are encouraged to address in their cover letter how their research, service, and/or life experiences prepare them to advance Dartmouth's commitment to diversity in service of academic excellence.