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We welcome applications from motivated individuals; however, it is essential that prospective candidates have a clear and well-defined career goal related to pursuing a Ph.D. or postdoctoral fellowship in data-driven computational mechanics. If there is uncertainty about your future aspirations or your reasons for pursuing advanced research in this field, we advise reconsidering your decision to reach out at this time. Our experience has shown that applicants with ambiguous career goals often face challenges, even after enrollment. While we celebrate many success stories, we have also learned from situations where unclear objectives led to less favorable outcomes. Therefore, we encourage prospective applicants to thoroughly reflect on their motivations before contacting our research group.

In our lab, we strive for success through hard work, smart strategies, and professionalism. If your goal is to build a recognized and respected career as a scientist, we are confident our lab can support you, though the journey will be demanding. However, if you are seeking a Ph.D. solely for the title, this lab may not be the best fit for you.

Please note that, due to the volume of inquiries we receive daily, we only respond to candidates who we believe are a good fit for our group. We retain all applications for future consideration and will contact candidates if a suitable position becomes available. It is important that applicants submit all necessary materials (transcripts, CV, and cover letter) when reaching out; incomplete applications may not be considered.

Welcome to join the innovative and dynamic research environment at the Bio-DMX Lab led by Dr. XQ Wang, where exciting experimental studies meet cutting-edge mechanics modeling and simulation. The projects of PhD positions span a wide spectrum of mechanics of biological soft materials, materials and structure design by AI and machine learning, data-driven mechanics of brain development and disorders, and data-enhanced computational modeling.
Required Qualifications:
– A B.S. in Engineering Mechanics, Mechanical Engineering, Materials Science, or a closely related field.
– An M.S. with relevant project experience and a strong publication record is a plus.
– Proficiency in programming such as MATLAB, C/C++, or Python. Experience in parallel computing and machine learning algrithms is advantageous.
– Experience with molecular dynamics simulations and finite element analysis.
– A broad knowledge of computational materials science and biophysics is beneficial.
Interested candidates are encouraged to submit their CV, academic transcripts, TOEFL or IELTS scores, and contact information for at least three professional references to Dr. XQ Wang at xqwang@uga.edu.

Undergraduate students seeking research opportunities, whether for pay or credit, are encouraged to reach out directly to graduate students or postdocs within the group whose research aligns with their interests. Alternatively, you may email to Dr. XQ Wang by xqwang@uga.edu with details about your research interests, relevant coursework, or previous research experience. Please note, however, that due to the high volume of inquiries, I may not be able to respond to every message individually. Undergraduate research is a key component of the UGA Experience and often serves as a transformative opportunity for our students. Our commitment to involving and supporting undergraduates in collaborative research and service learning promotes substantial intellectual, personal, and professional growth. Several scholarships and fellowships are available to support students engaged in this meaningful work.

UGA Center for Undergraduate Research Opportunities (CURO)
UGA Peach State LSAMP