Chemical Sensors-Data Analysis Strategies
This research develops data analysis methods like neural networks to improve chemical sensor accuracy in detecting hazardous substances in air and liquid.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: February 1, 2025 | May 1, 2025 | August 1, 2025 | November 1, 2025
Funding Amounts: Stipend approximately $99,200 per year plus $3,000 travel allowance; relocation assistance available for eligible awardees. Duration typically 2-3 years.
Summary: Supports postdoctoral research developing advanced multivariate data analysis methods to enhance chemical sensor systems for detecting hazardous substances in air and liquid.
Key Information: Open to U.S. citizens and permanent residents holding a doctoral degree; requires contacting a Research Adviser prior to application; health insurance provided.
Description
This fellowship opportunity at the Naval Research Laboratory (NRL) focuses on research to develop and apply multivariate data analysis techniques for chemical sensors and analytical instruments. The research aims to improve the selectivity, sensitivity, and robustness of chemical sensor systems used to monitor hazardous chemical species in air or liquid environments, which is critical for personal protection and environmental monitoring.
Key methods include neural networks, genetic algorithms, signal processing, and multivariate statistical approaches applied to pattern recognition and multivariate calibration. The research supports identification of chemical warfare agents, toxic industrial chemicals, and fires through detection systems employing arrays of semi-selective sensors.
Applications of these techniques include complex mixture analysis enhanced by multivariate calibration, demonstrated in technologies such as membrane inlet mass spectrometry and gas chromatography mass spectrometry.
Research Areas and Keywords
- Algorithms
- Artificial intelligence
- Chemical sensors
- Environmental toxicology
- Multivariate analysis
- Pattern analysis
- Signals and signal processing
