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 mobile computing, AI systems, and health monitoring platforms.
This fully funded position offers the opportunity to conduct research at the intersection of systems, machine learning, and healthcare innovation. You will work with faculty, postdocs, and collaborators across computer science, engineering, and clinical medicine to develop intelligent health platforms that translate from research prototypes to real-world deployment.
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
- Mobile health systems: smartphone and wearable sensing pipelines, continuous monitoring architectures, and edge computing for health applications.
- Machine learning for biosignals: deep learning and signal processing for physiological time series, activity recognition, and health state inference.
- On-device AI: efficient neural network deployment, model compression, and real-time inference on resource-constrained platforms.
- Health monitoring platforms: end-to-end system design from sensors to cloud, data pipelines, and user-facing applications.
- Brain-computer interfaces: signal processing and ML pipelines for neural data, real-time decoding, and closed-loop systems.
- Human-centered computing: user studies, clinical validation, and translation of research systems to real-world healthcare settings.
What We Offer
- Full funding: tuition coverage and competitive stipend throughout your PhD.
- Access to computing infrastructure, wearable sensing platforms, and clinical research partnerships.
- Interdisciplinary mentorship with faculty across CS, engineering, neuroscience, and medicine.
- Conference travel support, industry connections, and career mentorship.
Qualifications
- BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related field.
- Strong programming skills in Python, C/C++, or similar languages.
- Solid foundation in machine learning, signal processing, or systems programming.
- Experience with mobile/embedded development, data pipelines, or ML frameworks (PyTorch, TensorFlow).
- Interest in healthcare, wearable computing, or human-centered applications.
Additional Experience That Will Strengthen the Application
- Prior research experience or publications in mobile health, ubiquitous computing, or ML for health.
- Experience with embedded ML deployment (TFLite, ONNX, edge TPUs) or mobile app development.
- Familiarity with biosignal processing (ECG, EEG, PPG, IMU) or physiological data analysis.
- Background in human-subjects research, clinical collaborations, or IRB protocols.
Application Instructions
1. Email Dr. Tam Vu at tam.n.vu@dartmouth.edu with subject line "PhD Applicant CS [Your Name]" including:
- CV highlighting relevant coursework, projects, and research experience
- Brief statement (1 page) describing your research interests
- Links to code repositories, publications, or project demos (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.