Postdoc Fellow: Advanced Materials & ML for Energy Research

Texas A&M; Prairie View (TX); On-site; USD 60,000 - 75,000; Full time

Job summary

Prairie View A&M University is seeking a highly qualified Postdoctoral Researcher (PIER) in the Physics Department. The role focuses on materials science, including magnetic, optoelectronic, and thermoelectric measurements, with machine learning integration to improve design and prediction.

The appointment is initially one year, with potential renewal based on progress and funding. The candidate will work within a collaborative team, contribute to publications and proposals, and mentor graduate

Qualifications

• Ph.D. earned within the past three years is required.
• Experience applying ML and predictive modeling to materials science.
• Strong background in characterization techniques for magnetic, optoelectronic, and thermoelectric properties.

Responsibilities

• Conduct experimental research on novel materials with focus on magnetic, optoelectronic, and thermo-electronic properties.
• Develop and optimize measurement techniques for advanced materials characterization.
• Apply machine learning models to analyze data and predict material behavior.
• Collaborate with faculty, graduate students, and researchers on multidisciplinary projects.
• Contribute to writing research papers, grant proposals, and presenting findings at conferences.
• Assist in the mentoring of graduate and undergraduate students in the laboratory.
• Perform other duties as assigned.

Skills

Machine learning

Materials characterization

Education

PhD in Materials Science, Physics, Engineering or related field

Tools

PPMS

XRD

SQUID magnetometry

Optical spectroscopy

Scanning probe microscopy

Job description

Prairie View A&M University is seeking a highly qualified Postdoctoral Researcher (PIER) in the Physics Department. The role focuses on materials science, including magnetic, optoelectronic, and thermoelectric measurements, with machine learning integration to improve design and prediction.

The appointment is initially one year, with potential renewal based on progress and funding. The candidate will work within a collaborative team, contribute to publications and proposals, and mentor graduate