Post-doctoral fellow in Biomedical IoT and AI

The Arizona Center for Telemedicine and Digital Health invites applications for a Post‑Doctoral Fellow in Biomedical Internet of Things (IoT) and AI to design and develop IoT interfaces for biomedical sensors and embedded microcontrollers used with vital‑sign monitors. This is a hands‑on research and development role combining embedded firmware, sensor electronics, secure data pipelines, digital signal processing, AI, and clinical validation to accelerate next‑generation remote monitoring solutions.

• Design and implement embedded firmware for microcontrollers (ARM Cortex‑M, ESP
  32, etc.) to acquire, preprocess, and transmit physiological signals.
• Integrate biomedical sensors (ECG, PPG, SpO₂, temperature, respiration, accelerometers) with analog front ends and ADCs.
• Develop low‑power IoT interfaces using BLE, Wi‑Fi, LoRa, and MQTT/HTTP for reliable, secure data transfer to cloud and edge systems.
• Prototype hardware and electronics including sensor interfacing, signal conditioning, and basic PCB bring‑up.
• Build end‑to‑end data pipelines
  : embedded → gateway → cloud; implement data serialization, buffering, and fault tolerance.
• Validate performance through bench testing and clinical pilot studies with vital‑sign monitors; collaborate with clinicians and clinical engineers.
• Ensure security and compliance
  : implement encryption, authentication, and HIPAA‑aware data handling practices.
• Document and disseminate results via technical reports, peer‑reviewed publications, and presentations.
• Mentor students and collaborate across multidisciplinary teams (clinicians, software engineers, regulatory specialists).

• PhD in Electrical Engineering, Computer Engineering, Biomedical Engineering, or related field completed within the last 5 years.
• Strong embedded systems experience
  : C/C++, RTOS, device drivers, low‑level peripheral control (ADC, DMA, I2C, SPI, UART).
• Hands‑on experience with microcontrollers (ARM Cortex‑M family, ESP
  32, nRF
  52, or similar).
• Proven sensor integration skills
  : analog front‑end design, signal conditioning, sampling theory, and noise mitigation.
• Wireless and IoT protocols
  : BLE, Wi‑Fi, LoRa, MQTT, HTTP, and experience with gateway/cloud integration.
• Data processing and scripting
  : proficiency in Python or MATLAB for signal processing, analysis, and visualization.
• Experience with medical device or clinical research environments or demonstrated ability to work with clinical partners.
• Strong written and verbal communication and a record of technical publications or demonstrable project deliverables.

• Prior work with vital‑sign monitors or physiological signal acquisition systems.
• Experience with secure data architectures and familiarity with HIPAA, GDPR, or equivalent privacy frameworks.
• PCB layout and hardware debugging experience.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerized services.
• Machine learning or advanced signal processing applied to physiological data.
• Experience mentoring students or leading small engineering teams.

• Position type
  :
  Full‑time post‑doctoral fellowship.
• Duration
  : 1–3 years, renewable based on performance and funding.
• Location
  : on‑site presence required for hardware prototyping and clinical testing.
• Compensation
  :
  Competitive salary commensurate with experience and institutional postdoc scales; benefits include health insurance, retirement plan, and professional development support.
• Start date
  :
  Flexible; preferred start within 1–2 months of offer.

Please submit the following:

• Curriculum vitae including publication list.
• Cover letter describing relevant experience and interest in telemedicine and digital health.
• Research statement (1–2 pages) outlining past work and proposed contributions to the center.
• Contact information for three references
  .