Postdoctoral Researcher, Advanced Materials & ML

tamus; Prairie View (TX); On-site; USD 55,000 - 70,000; Full time

Job summary

Prairie View A&M University, in the Physics Department, seeks a Postdoctoral Fellow to join our Materials Science research team focused on magnetic, optoelectronic, and thermoelectric materials. The role emphasizes integrating machine learning and predictive modeling to enhance material design and performance prediction.

The appointment is one year, in residence, with potential renewal for a second year based on progress and funding.

Qualifications

• PhD awarded within the past three years.
• Experience with machine learning and predictive modeling in materials science or related fields.
• Strong background in materials characterization techniques (magnetic, optoelectronic, thermoelectric).

Responsibilities

• Conduct experimental research on novel materials with a focus on magnetic, optoelectronic, and thermo-electronic properties.
• Develop and optimize measurement techniques for advanced materials characterization.
• Apply machine learning models to analyze experimental 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 mentoring graduate and undergraduate students in the laboratory.
• Perform other duties as assigned.

Skills

Machine learning

Predictive modeling

Materials characterization

Independent research

Communication skills

Education

Ph.D. 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, in the Physics Department, seeks a Postdoctoral Fellow to join our Materials Science research team focused on magnetic, optoelectronic, and thermoelectric materials. The role emphasizes integrating machine learning and predictive modeling to enhance material design and performance prediction.

The appointment is one year, in residence, with potential renewal for a second year based on progress and funding.