Tao Research Group in the Theoretical and Computational Chemistry (TCC) 
program at Southern Methodist University (SMU) invites applications for 
a Postdoctoral Research Fellow in molecular stochastic modeling. 
This is an exciting opportunity to contribute to cutting-edge research 
focused on the development and application of stochastic differential 
equation (SDE) methods for modeling mechanically activated photochemistry (MAPC) 
and biomolecular processes. The successful candidate will play a key role 
in methodological development, with a particular focus on integrating 
machine learning techniques to manage high-dimensional data and 
improve modeling accuracy. Collaboration is a cornerstone of this position; 
the candidate will work closely with experimentalists in chemiluminescence 
and mechanochemistry, as well as with mathematicians specializing 
in stochastic differential equations and artificial intelligence. 

Key Responsibilities:
1. Develop and implement advanced SDE methods for modeling molecular-level phenomena.
2. Design and apply machine learning frameworks such as diffusion models 
   and flow matching to enhance simulation accuracy and computational scalability.
3. Leverage large-scale simulation and experimental datasets to construct 
   predictive models for MAPC and biomolecular mechanisms.
4. Collaborate within a multidisciplinary team to integrate experimental 
   insights into robust theoretical and computational models.
5. Prepare high-impact scientific manuscripts and present research 
   outcomes at leading international conferences.

Qualifications:
1. Ph.D. in mathematics, chemistry, biophysics, physics, or a related 
   discipline, with a strong emphasis on stochastic modeling and machine learning.
2. Demonstrated proficiency in the development and application of 
   stochastic differential equation frameworks for modeling complex stochastic processes.
3. Strong programming skills in Python, R, or similar languages, 
   and experience with high-performance computing environments.
4. Proficiency in machine learning, with an emphasis on generative AI 
   techniques such as diffusion models and flow matching are highly desired.
5. Excellent analytical, organizational, and communication skills, 
   with a proven track record of publishing scientific research.


About Us:
Tao research group is committed to excellence in research and education, 
offering a dynamic and inclusive environment for scientific discovery. 
Our research interest covers theoretical and computational methods 
development and their applications regarding biomolecular simulations, 
protein allostery, and enzyme catalysis. 
Please see our website http://faculty.smu.edu/ptao.
Located in Dallas, TX, our institution is at the heart of a thriving 
scientific community, providing ample opportunities for collaboration 
and innovation.

Interested candidates should submit a cover letter highlighting their 
research interests and experience, a detailed CV, and contact information 
for three references to Dr. Peng Tao through email (ptao+/-smu.edu).