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We are seeking a highly motivated researcher to join our team for conducting cutting-edge theoretical and experimental research on super-resolution imaging for two- and three-point sources. The candidate will also explore the enhancement of super-resolution techniques using machine learning methods. This position offers the opportunity to collaborate with a dynamic team of researchers and contribute to advancements in imaging technologies.

Responsibilities:

Theoretical and Experimental Research:

•    Design and execute theoretical models, collaborate on experimental setups and measurements, for super-resolution imaging of two- and three-point sources.

•    Analyze and interpret experimental data to validate theoretical predictions.

•    Develop innovative methods to push the boundaries of super-resolution imaging.

Machine Learning Integration:

•    Investigate and implement machine learning algorithms to enhance super-resolution imaging techniques.

•    Collaborate with machine learning experts to integrate advanced computational methods into experimental workflows.

Technical Proficiency:

•    Utilize LaTeX for the preparation of technical documents, research papers, and presentations.

•    Employ Python and Matlab for data analysis, simulation, and algorithm development.

•    Use PowerPoint for creating engaging presentations.

Dissemination of Research:

•    Prepare and submit research findings to high-impact conferences and peer-reviewed journals.

•    Present research outcomes at national and international conferences, workshops, and seminars.

Qualifications

• Doctoral degree in Quantum Physics, Optics, or related fields.

• Strong research background in quantum physics.

• Experience with optical imaging.

• Experience with machine learning techniques.

• Proficiency in LaTeX, Python, Matlab, Microsoft Word, and PowerPoint.

• Excellent written and verbal communication skills.

• Ability to work collaboratively in a multidisciplinary team environment.

Application Process
Interested candidates should submit the following materials:

• A detailed CV highlighting relevant experience and publications.

• A cover letter describing your research interests and how they align with this position.

• Application Deadline: November 15th 2025. 

For detailed information, please contact Prof. Xiaofeng Qian at xqian6@stevens.edu