Professional Research Assistant

Job Summary BioServe Space Technologies, within the College of Engineering and Applied Science (CEAS) at CU Boulder, is seeking a Professional Research Assistant to participate in a project using Python to implement a machine learning approach for modeling G-induced loss of consciousness (G-LOC) in pilots. G-LOC is a dangerous condition that occurs when pilots in high performance aircraft pull high G-levels. Physiological data has been collected from participants in a centrifuge (e.g., Electrocardiogram, Electroencephalogram, Eye-tracking, Respiration, etc.) and is being used to predict G-LOC in advance. Machine Learning approaches being implemented include traditional machine learning approaches, such as Random Forest, Linear Discriminant Analysis, K-Nearest Neighbors, Support Vector Machine, and more. More advanced approaches are also being explored, such as neural networks and other deep learning classifiers. We will be exploring how well models can generalize to unseen participants, and we may also be exploring the importance of each individual biosignal (e.g., Electrocardiogram or eye-tracking) in predicting G-LOC. This project will involve a lot of coding in Python and working with physiological data. CU is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities. Who We Are The bioastronautics lab is developing technologies to measure and mitigate the body's adaptations to extreme stressors with the primary motivation to advance human space exploration, as well as aviation, and individuals in extreme environments here on Earth. Our methods include fabrication, modeling, data mining, and human subject experimentation. Thus, by focusing our research on human health and performance in extreme environments, we are advancing the state of the art for Earth-based applications in several diverse fields. What Your Key Responsibilities Will Be In this role you will be responsible for developing and maintaining a machine learning pipeline, designed to predict G-induced loss of consciousness (G-LOC) from physiological, behavioral, and demographic data. You will be partially managing a team of undergraduate student researchers and developing deliverables for the Air Force Research Laboratory. What You Should Know Anticipated start date is June 1 through August 31, 2026. We are not able to provide H-1B or J-1 visa sponsorships at this time for this appointment. What We Can Offer The starting salary range for this position is $52,000-$54,080 annually. Benefits At the University of Colorado Boulder , we are committed to supporting the holistic health and well-being of our employees. Our comprehensive benefits package includes medical, dental, and retirement plans; generous paid time off; tuition assistance for you and your dependents; and an ECO Pass for local transit. As one of Boulder County's largest employers, CU Boulder offers an inspiring academic community and access to world-class outdoor recreation. Explore additional perks and programs through the CU Advantage program. Be Statements Be adventurous. Be game-changing. Be Boulder. What We Require Bachelor's degree. Experience with Python or another object-oriented programming language. What We Would Like You to Have Experience with machine learning and deep learning methods, or experience with physiological data streams. Special Instructions To apply, please submit the following materials as individual files: Cover Letter describing your interest in the position and prior research experience. Resume/CV that includes all relevant experience and a list of publications. (Optional)

Transcripts/Proof of Degree :

If you are selected as the finalist, your degree will be verified by the CU Boulder Campus Human Resources department using an approved online vendor. If your degree was obtained outside of the United States, please submit an English-translated version (if applicable) as an Optional attachment. During the application process, you will be asked to provide the name and email address for one reference, from whom we may request a confidential letter of recommendation at some point later in the search process. For full consideration, please apply by May 13, 2026 .

Note:

Application materials will not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs . In compliance with the Colorado Job Application Fairness Act, in any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

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