Researcher - Artificial Intelligence and Machine Learning
Listed on 2026-09-09
-
Research/Development
Data Scientist, AI Business & Operations
Researcher - Artificial Intelligence and Machine Learning
Posting #5708
Location:
San Diego
Position Status:
Full-time temporary, Part-time temporary
Position Type:
Staff, Shiley-Marcos School of Engineering
Position Title & Department:
Researcher - Artificial Intelligence and Machine Learning;
School of Engineering
Department
Description:
The University of San Diego's Shiley-Marcos School of Engineering does more than develop world-class engineers and computer scientists in a nationally recognized program. We help these bright minds develop into Changemakers with the global perspective, social awareness and leadership skills to make a difference in the world.
University
Description:
The University of San Diego, an engaged and contemporary Catholic institution, was founded by the Diocese of San Diego and the Society of the Sacred Heart in 1949. Governed by an independent board of trustees since 1972, USD remains committed to a liberal arts education grounded in the Catholic intellectual tradition and the pursuit of truth, goodness and beauty. Inspired by this centuries old tradition of Catholic higher education, the University welcomes people of all faith traditions and any, or no, religious background.
The future success of USD relies on the contributions of those who seek to foster the development of engaged global citizens and an earnest confrontation of humanity’s urgent challenges .
Detailed
Description:
This is a full-time or part-time temporary, benefit-based or non-benefit-based position with an anticipated end date of August 31, 2027.The appointment is renewable at the discretion of the University and dependent upon performance and continued funding.
The University of San Diego’s Department of Electrical Engineering is seeking a researcher to contribute to an NSF-funded project focused on data-centric artificial intelligence (AI) and wearable biosensors for enhancing student learning, engagement, and stress management.
The project combines wearable physiological sensing with machine learning and data-centric AI methods to develop reliable models of student engagement and stress and ultimately provide meaningful, data-driven insights for educators.
The researcher will work closely with the Principal Investigator, Dr. Nadieh Moghadam, and other members of the research team.
Duties and Responsibilities:
- Processing and analyzing physiological signals from wearable biosensors, including heart rate and electrodermal activity (EDA).
- Developing, implementing, and evaluating machine learning and AI models using public and project-generated datasets.
- Applying data-centric AI techniques, including data cleaning, feature engineering, augmentation, and multimodal data analysis.
- Evaluating and working with wearable sensing technologies.
- Supporting development and evaluation of an adaptive application for translating AI results into actionable insights for instructors.
- Support human-subject research activities, including participant recruitment, wearable biosensor deployment, physiological data collection during classroom studies, and organization and analysis of collected data in accordance with the approved IRB protocol.
- Conducting literature reviews and documenting research methods and results.
- Contributing to research publications, presentations, and dissemination of project findings.
- Collaborating with undergraduate researchers and other members of the research team.
Special Conditions of Employment:
Background check: Successful completion of a pre-employment background check.
Degree Verification Requirement
:
Persons offered employment in this position will be required to provide official education transcripts for degree verification purposes.
Job Requirements:
Minimum Qualifications:
- Bachelor’s degree or higher in Electrical/Computer Engineering, Computer Science, Data Science, Biomedical Engineering, or a related field.
- Programming experience in Python, MATLAB, or similar environments.
- Background or demonstrated interest in machine learning, artificial intelligence, signal processing, or data analysis.
- Strong analytical, communication, and problem-solving skills.
- Ability to work independently and collaboratively within a…
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