The postdoctoral fellow will conduct, report and present research in his/her field of study under the supervision of a faculty mentor. This is a training position, and is not expected to be a permanent position.

About the lab:

The Brahmachari Lab, in the Department of Biochemistry and Molecular Biology at the University of Texas Medical Branch (UTMB), and affiliated with the Sealy Institute of Drug Discovery, combines statistical physics, molecular simulations, and physics-informed AI modeling to understand how genomes are organized, regulated, and dynamically remodeled. Current projects span energy-landscape modeling of chromosome folding, non-equilibrium/active mechanisms in chromatin dynamics, and development of physics-grounded AI models for genomic data.

Essential Job Functions:

• Design, implement, and conduct advanced theoretical and computational research studies, using established methods and, in many cases, developing new approaches.
• Build and apply quantitative models to analyze complex phenomena relating genome structure to function, integrating simulation, statistical analysis, and machine learning techniques as appropriate.
• Analyze, interpret, and validate research data against experimental observations; maintain organized records of methods, code, and results.
• Prepare data, figures, and findings for presentation at scientific conferences and for manuscript preparation; publish results in peer-reviewed research journals.
• Provide guidance and mentorship to graduate students, junior researchers, and trainees in the lab as needed.
• Stay current with relevant scientific literature and emerging methods in the field.
  

Minimum Qualifications:

• Ph.D., M.D. or Doctoral equivalent in any field. Scientific research experience.
  

Preferred Qualifications:

• Strong foundation in mathematical sciences, with comfort working across statistical mechanics, statistics, dynamics, and coarse-grained modeling.
• Demonstrated coding proficiency (e.g., Python, C/C++, or similar), ideally reflected in a GitHub portfolio or other accessible record of software work.
• A track record of scholarly activity, such as peer-reviewed publications, in biophysics or a closely related field.
• Familiarity with molecular simulation methods (e.g., molecular dynamics, coarse-grained modeling) and/or machine learning approaches, with interest in applying them to biological questions.
• Experience with large datasets (e.g., genomic data) and high-performance computing environments.
• Strong written and verbal communication skills, with the ability to present research clearly to varied audiences.
• Ability to work both independently and collaboratively in an interdisciplinary research environment.
  

Salary:
Commensurate with experience using the NIH standard

EQUAL EMPLOYMENT OPPORTUNITY:

UTMB Health strives to provide equal opportunity employment without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, genetic information, disability, veteran status, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. As a Federal Contractor, UTMB Health takes affirmative action to hire and advance protected veterans and individuals with disabilities.