Summary:
The University of Georgia (UGA) invites applications for a Postdoctoral Research Associate to join an interdisciplinary research program focused on developing AI-enabled surface-enhanced Raman spectroscopy (SERS) for precision molecular measurement and biophysical discovery.
Postdoctoral Research Associate in AI-Enabled Surface-Enhanced Raman Spectroscopy (SERS), US
Designation:
Postdoctoral Research Associate
Table:
| Field | Details |
|---|---|
| Research Area | AI-enabled Surface-Enhanced Raman Spectroscopy (SERS) |
| Location | University of Georgia, Department of Physics |
| Eligibility/Qualification | Ph.D. in Physics, Chemistry, Materials Science, Biomedical Engineering, or related field |
| Job Type | Full-Time |
| Funding Source | Gordon and Betty Moore Foundation |
Research Area:
The position focuses on applying SERS techniques in various applications such as nucleic acid analysis, single-cell spectroscopy, plant metabolomics, environmental monitoring, and materials characterization.
Job Description:
The postdoctoral researcher will work primarily under the mentorship of Prof. Yiping Zhao and will be responsible for:
- Research & Experimental Development (45%)
- Conduct Raman/SERS experiments
- Develop and validate measurement strategies ensuring reproducibility.
- Data Analysis & Machine Learning (25%)
- Apply machine learning/statistical models to spectral data
- Perform computational analysis and validation
- Scholarly Dissemination & Reporting (15%)
- Publish results and present at conferences
- Contribute to required funding reports
- Mentoring & Collaboration (10%)
- Mentor students and participate in interdisciplinary activities
- Professional Development & Service (5%)
- Engage in training, outreach, and career-development activities
Eligibility/Qualification:
- Required:
- Ph.D. (or equivalent terminal degree) in a relevant field completed by the start date
- Hands-on experimental experience in SERS, including substrate preparation and data analysis
- Evidence of research productivity through peer-reviewed publications or significant contributions
- Preferred:
- Experience with microfluidics, chromatography, electrophoresis, or related techniques
- Machine learning, statistical modeling, or data-driven methods in spectroscopic datasets
- Background in nanofabrication, plasmonic materials, or separation science
- Proficiency in Python, MATLAB, or similar programming languages
- Interest in interdisciplinary research
How to Apply:
Applicants should submit the following:
- Curriculum vitae
- Cover letter describing research interests and fit for the position
- Three recommendation letters
For detailed application procedures, visit: Application Procedure
Last Date for Application:
Review of applications will begin immediately and continue until the position is filled. Please submit your application as soon as possible.
