At Dartmouth's Cluster for Improving Healthcare Outcomes through Sensory Technology
Description
The Cluster for Improving Healthcare Outcomes through Sensory Technology at Dartmouth is recruiting PhD students focused on wearable sensing, embedded systems, and signal processing for healthcare applications.
This fully funded position offers the opportunity to conduct research at the intersection of electrical engineering, biomedical sensing, and healthcare innovation. You will work with faculty, postdocs, and collaborators across engineering, computer science, and clinical medicine to develop wearable systems that translate from laboratory prototypes to real-world health impact.
PhD students may be admitted through the Department of Computer Science or Thayer School of Engineering. Start date is Fall 2026, with applications reviewed on a rolling basis.
Research Areas
- Wearable biosignal sensing: low-noise analog front-ends for ECG, EEG, EMG, PPG, bioimpedance, and motion.
- Miniaturized sensor systems: compact, power-efficient PCB designs for body-worn health monitors.
- Embedded signal processing: on-device algorithms for real-time biosignal analysis and artifact rejection.
- Skin-electrode interfaces: novel electrode materials, dry/textile electrodes, and contact optimization.
- Low-power system design: power management, energy harvesting, and ultra-low-power techniques for continuous monitoring.
- Human-centered validation: bench characterization, human-subject studies, and clinical translation.
What We Offer
- Full funding: tuition coverage and competitive stipend throughout your PhD.
- Access to hardware prototyping labs, cleanroom fabrication, and clinical research infrastructure.
- Interdisciplinary mentorship with faculty across CS, engineering, neuroscience, and medicine.
- Conference travel support, industry connections, and career mentorship.
Qualifications
- BS or MS in Electrical Engineering, Computer Engineering, Biomedical Engineering, or related field.
- Strong foundation in analog/mixed-signal circuit design and electronics fundamentals.
- Hands-on experience with PCB design tools (Altium, KiCad, Eagle, or similar).
- Familiarity with bench instrumentation (oscilloscopes, signal generators, spectrum analyzers).
- Programming skills in embedded C/C++, Python, or MATLAB.
Additional Experience That Will Strengthen the Application
- Prior research experience or publications in wearables, biosensors, or related areas.
- Experience with embedded firmware development (ARM Cortex-M, ESP32, nRF, etc.).
- Exposure to machine learning for time-series or physiological signals.
- Background in human-subjects research or clinical collaborations.
Application Instructions
1. Email Dr. Tam Vu at tam.n.vu@dartmouth.edu with subject line "PhD Applicant EE [Your Name]" including:
- CV highlighting relevant coursework, projects, and research experience
- Brief statement (1 page) describing your research interests
- Links to relevant projects or portfolio materials (optional)
2. Apply to Dartmouth's PhD program in Computer Science (cs.dartmouth.edu) or Engineering (engineering.dartmouth.edu). Mention your interest in CIHOST and Dr. Tam Vu's research group.
Early contact is encouraged. Review begins immediately and continues until positions are filled.
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.
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.