Post-Doctoral Research Associate, Department of Biosystems Engineering & Soil Science: UTIA
- University of Tennessee
- Location: Knoxville, TN
- Job Number: 7373436
- Posting Date: Newly posted
- Application Deadline: Open Until Filled
Job Description
Job Description
This position is part of a cutting-edge project investigating the conversion of nitrogen in air to nitrogen fertilizer using plasma technologies, and the practical applications.
The successful candidate will contribute to multiple aspects of the project, including:
Thermodynamic and kinetic analysis of chemical reactions in plasma environments
Development of catalysts tailored for plasma-assisted processes
System integration and performance optimization
Techno-economic analysis of the developed systems
This is a grant-funded position and is contingent upon the continued funding of the grant.
Responsibilities
The successful candidate is expected to conduct experiments outlined in the job description, to analyze data, and to write project reports and manuscripts for peer-reviewed publications.
The successful candidate will contribute to multiple aspects of the project, including:
Thermodynamic and kinetic analysis of chemical reactions in plasma environments
Development of catalysts tailored for plasma-assisted processes
System integration and performance optimization
Techno-economic analysis of the developed systems
Qualifications
Required Qualifications:
Education:
Ph.D. in Agricultural/Biosystems Engineering, Chemical Engineering, Mechanical Engineering, or a closely related field.
Experience/Knowledge, Skills, & Abilities:
Solid understanding of plasma physics and chemistry.
Demonstrated experience in applied chemical catalysis.
Hands-on experience with high-voltage plasma technologies.
Excellent written and spoken communication skills.
Strong motivation, independence, and the ability to work effectively in a collaborative team environment.
Preferred Qualifications:
Applicants with experience in one or more of the following areas will be strongly preferred:
Electrical characterization of plasma discharges
Plasma diagnostics via optical emission or Raman spectroscopy
Chemical product analysis (e.g., GC, UV-Vis, FTIR)
Application of AI or machine learning techniques to reaction system optimization
Techno-economic analysis
This position is part of a cutting-edge project investigating the conversion of nitrogen in air to nitrogen fertilizer using plasma technologies, and the practical applications.
The successful candidate will contribute to multiple aspects of the project, including:
Thermodynamic and kinetic analysis of chemical reactions in plasma environments
Development of catalysts tailored for plasma-assisted processes
System integration and performance optimization
Techno-economic analysis of the developed systems
This is a grant-funded position and is contingent upon the continued funding of the grant.
Responsibilities
The successful candidate is expected to conduct experiments outlined in the job description, to analyze data, and to write project reports and manuscripts for peer-reviewed publications.
The successful candidate will contribute to multiple aspects of the project, including:
Thermodynamic and kinetic analysis of chemical reactions in plasma environments
Development of catalysts tailored for plasma-assisted processes
System integration and performance optimization
Techno-economic analysis of the developed systems
Qualifications
Required Qualifications:
Education:
Ph.D. in Agricultural/Biosystems Engineering, Chemical Engineering, Mechanical Engineering, or a closely related field.
Experience/Knowledge, Skills, & Abilities:
Solid understanding of plasma physics and chemistry.
Demonstrated experience in applied chemical catalysis.
Hands-on experience with high-voltage plasma technologies.
Excellent written and spoken communication skills.
Strong motivation, independence, and the ability to work effectively in a collaborative team environment.
Preferred Qualifications:
Applicants with experience in one or more of the following areas will be strongly preferred:
Electrical characterization of plasma discharges
Plasma diagnostics via optical emission or Raman spectroscopy
Chemical product analysis (e.g., GC, UV-Vis, FTIR)
Application of AI or machine learning techniques to reaction system optimization
Techno-economic analysis
