Research Opportunities Available

We are seeking motivated students to join our cutting-edge research programs in artificial intelligence, wireless communications, imaging systems, and computational biology. Multiple positions are available at both undergraduate and graduate levels.

Undergraduate Student Researcher Positions

AI-Driven Design of Cancer Theranostics

Start Date: September 1, 2025

Hours: 20 hours per week (flexible scheduling)

Rate: $15/hour

Location: BRIC and Remote Work Options

Funding: National Institutes of Health – National Cancer Institute

Join our project developing AI-driven approaches to accelerate targeted cancer therapy design. This innovative research integrates advanced artificial intelligence methodologies to create novel bispecific molecules that simultaneously target critical paired enzyme systems in cancer cells, overcoming traditional therapy resistance mechanisms.

Key Responsibilities:

  • Python programming for AI and machine learning model development
  • Computational biology implementation and algorithm optimization
  • Participate in online meetings with biomedical scientist collaborators
  • Contribute to presentation preparation for research conferences and NIH stakeholders

Ideal Candidate: Junior or senior undergraduate in Engineering, Computer Science, Biology, or related field with Python programming experience and interest in AI/machine learning applications in healthcare.

AI-Enhanced Predictive Analytics and Interference Mitigation for Wireless Communications

Start Date: September 1, 2025

Hours: 20 hours per week (flexible scheduling)

Rate: $15/hour

Location: BRIC and Remote Work Options

Funding: Department of Defense (DoD)

Eligibility: US citizens only

Join our research project revolutionizing wireless communication systems through advanced AI transformer models and predictive analytics. This project develops next-generation solutions that combine AI-powered predictive analytics with real-time interference detection and mitigation.

Key Responsibilities:

  • Python and MATLAB programming for AI model development and signal processing
  • Support hardware implementation and participate in real-world field testing
  • Participate in online meetings with DoD personnel and collaborating researchers
  • Contribute to presentation preparation for conferences and research meetings

Ideal Candidate: Junior or senior undergraduate in Engineering, Computer Science, or related field with Python/MATLAB programming experience and interest in wireless communications, signal processing, or machine learning.

AI-Enhanced Real-Time Thermal and Visible Light Military Imaging

Start Date: September 1, 2025

Hours: 20 hours per week (flexible scheduling)

Rate: $15/hour

Location: BRIC and Remote Work Options

Funding: Department of Defense (DoD)

Eligibility: US citizens only

Join our project developing advanced image processing techniques for uncooled thermal long-wavelength infrared (LWIR) cameras to enhance imagery for field operations. This cutting-edge research addresses critical limitations of thermal imaging systems through AI/ML-driven solutions.

Key Responsibilities:

  • Python programming for AI model development and real-time image/video processing
  • Support hardware implementation and participate in field testing of dual-sensor imaging systems
  • Participate in online meetings with DoD personnel and collaborating researchers
  • Contribute to presentation preparation for research conferences and military stakeholders

Ideal Candidate: Junior or senior undergraduate in Engineering, Computer Science, or related field with Python programming experience and interest in image/video processing, computer vision, or machine learning.

Graduate Research Assistantship Positions

AI-Driven Design of Cancer Theranostics

Start Date: September 1, 2025

Compensation: Graduate assistantship stipend and tuition waiver

Location: BRIC (Baylor Research and Innovation Collaborative)

Funding: National Institutes of Health – National Cancer Institute

We seek a highly motivated graduate student to join our research program developing AI-driven approaches to accelerate targeted cancer therapy design using graph-string transformers and reinforcement learning algorithms to navigate vast chemical spaces.

Key Responsibilities:

  • Lead independent research tasks in advanced Python programming and machine learning
  • Design and implement computational biology algorithms and optimization strategies
  • Conduct literature reviews and contribute to research publications
  • Present research findings at conferences and to NIH stakeholders
  • Mentor undergraduate researchers working on related projects

Ideal Candidate: Graduate student in Engineering, Computer Science, Biology, Bioinformatics, or related field with strong programming expertise in Python and machine learning frameworks, background in computational biology or drug discovery, and demonstrated research experience.

AI-Enhanced Predictive Analytics and Interference Mitigation for Wireless Communications

Start Date: September 1, 2025

Compensation: Graduate assistantship stipend and tuition waiver

Location: BRIC (Baylor Research and Innovation Collaborative)

Funding: Department of Defense (DoD)

Eligibility: US citizens only

We seek a highly motivated graduate student to join our research program revolutionizing wireless communication systems through advanced AI transformer models addressing critical challenges in spectrum efficiency, interference management, and adaptive resource allocation.

Key Responsibilities:

  • Lead independent research initiatives in advanced Python and MATLAB programming
  • Design and implement novel transformer architectures for wireless communication applications
  • Conduct comprehensive literature reviews and contribute to peer-reviewed publications
  • Support hardware implementation and lead real-world field testing campaigns
  • Present research findings at major conferences and to defense stakeholders

Ideal Candidate: Graduate student in Electrical Engineering, Computer Science, or related field with strong programming expertise in Python and MATLAB, background in wireless communications or signal processing, and demonstrated research experience with potential for security clearance eligibility.

AI-Enhanced Real-Time Thermal and Visible Light Military Imaging

Start Date: January 15, 2026

Compensation: Graduate assistantship stipend and tuition waiver

Location: BRIC (Baylor Research and Innovation Collaborative)

Funding: Department of Defense (DoD)

Eligibility: US citizens only

We seek a highly motivated graduate student to join our research program developing advanced image processing techniques for uncooled thermal LWIR cameras using state-of-the-art computer vision and machine learning techniques for real-time sensor fusion.

Key Responsibilities:

  • Lead independent research activities in advanced Python programming for real-time image/video processing
  • Design and implement novel sensor fusion algorithms and optimization strategies
  • Conduct comprehensive literature reviews and contribute to peer-reviewed publications
  • Lead hardware implementation efforts and coordinate field testing
  • Present research findings at major conferences and to military stakeholders

Ideal Candidate: Graduate student in Electrical Engineering, Computer Science, Computer Engineering, or related field with strong programming expertise in Python and computer vision libraries, background in image/video processing or machine learning, and demonstrated research experience with potential for security clearance eligibility.

How to Apply

For Undergraduate Positions: Contact Dr. Liang (Leon) Dong at liang_dong@baylor.edu with your resume, unofficial transcript, and a brief statement of interest explaining your motivation for the specific research area.

For Graduate Positions: Contact Dr. Liang (Leon) Dong at liang_dong@baylor.edu with your CV, transcripts, research statement, and contact information for three references.

Baylor University is an Equal Opportunity/Affirmative Action employer committed to excellence through diversity.

© Liang (Leon) Dong, 2025