Weekend Machine Learning Postdoc Jobs in Arizona

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.

Key Responsibilities

• Design and implement embedded firmware for microcontrollers (ARM Cortex‐M, ESP32, 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).

Required Qualifications

• 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, ESP32, nRF52, 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.

Preferred Qualifications

• 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.

Appointment Details and Benefits

• 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.
• Support for conference travel and research expenses.

 Join us to be at the forefront of biomedical IoT innovation! Your expertise will help shape the future of personalized healthcare solutions through groundbreaking AI research. This is a paid position committed to fostering your professional growth while making meaningful contributions to health technology advancements.