Dr. Shen welcomes talented and highly motivated students to join his research group at Texas Tech University. Future recruitment opportunities will be subject to the availability of pending grant support. The group focuses on developing practical and sustainable materials and processes for selective separation and resource recovery in environmental and energy-related applications.
Current research areas include:
Supported by federal agencies, including NSF, EPA, and DOE, these projects provide students with opportunities to engage in interdisciplinary research, present their work at national and international conferences, and publish in peer-reviewed journals. Applicants with backgrounds in environmental engineering, chemical engineering, materials science, membrane processes, polymer synthesis, or water and wastewater treatment are encouraged to apply. Students with diverse academic and research experiences who are eager to develop innovative solutions for environmental and energy challenges are welcome. Prospective students are encouraged to contact Dr. Shen directly and email their CV and academic transcript to yuexiao.shen@ttu.edu.
The recipients of the Koh Family Scholarships (preference to new incoming Ph.D. students) will receive $38,000/year (plus tuition) for up to four years of graduate study or in combination with other awards and research assistantships, up to $44,000/year. Recipients will be selected on the basis of outstanding scholarship, exemplary character and meaningful extracurricular activities. A 1-page plan on outreach and extracurricular activities will be required for the nomination. Must maintain a minimum GPA of 3.5. Preference will be given to new incoming Ph.D. students. Recipients will pursue full time study in an engineering discipline in graduate level courses for an advanced degree. Students need to first apply for admission to the graduate program through Texas Tech Graduate School. Nominations for the Koh Scholarship must be submitted by a faculty member in the Whitacre Jr. College of Engineering using this form.
Distinguished Graduate Student Assistantships (DGSA) are offered by Texas Tech University to attract high-quality applicants into our doctoral programs. Awards will be $25,000/year plus tuition and fee waivers for up to 4 years, contingent upon satisfactory academic progress. Students may not apply; they must be nominated. The nomination must clearly indicate how the nominee's qualifications rank among top applicants in the discipline (supported by appropriate metrics).
Recruitment Fellowships provide supplements to department stipends in order to make competitive offers to top applicants. Fellowships are $5,000/yr for four years for Ph.D. students and $5,000/yr for two years for master's students. Students DO NOT apply for these fellowships, but nominated by faculty members.
Graduate Access and Engagement Recruitment Fellowship aim to increase participation of domestic underserved populations in our graduate programs through multifactorial means. Nominators must upload a letter that demonstrates how their nominee increases participation of individuals from underserved populations. Nominees must be domestic and meet one or more of the following criteria: first-generation college student, socioeconomically disadvantaged, multilingual, increases geographical representation. The package includes: Waiver of application fee; $5,000/yr stipend supplement for up to 2 years for Master's and 4 years for Ph.D. students; A $500 research/travel allowance.
Graduate students can apply to their academic department and the Graduate School for general fellowship opportunities at Texas Tech University. The Graduate School provides a number of fellowship opportunities to new and continuing students. The full list of Graduate School General Fellowships is available here. Students may self-apply with typical awards ranging from $3,000–$5,000/yr.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.