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Open Funded Research Position

Minah Lee SEDIS Lab Fully Funded PhD Positions in CS and AI at UT Dallas – Spring 2027

The University of Texas at Dallas

Professor Minah Lee is recruiting fully funded Ph.D. students for Spring 2027 in UT Dallas Electrical and Computer Engineering, focusing on machine learning, intelligent sensing, uncertainty-aware inference, multi-agent systems and autonomous systems. Apply by August 22, 2026 at 11:59 p.m. CDT.

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Assistant Professor Minah Lee is recruiting fully funded Ph.D. students for Spring 2027 in the Department of Electrical and Computer Engineering at The University of Texas at Dallas.

The openings are in the Sensing-to-Decision Intelligent Systems (SEDIS) Lab. The lab develops intelligent systems that turn sensing into reliable decision-making by combining adaptive sensing, uncertainty-aware machine learning, embedded intelligence and distributed multi-agent autonomy.

The Spring 2027 recruitment is particularly focused on machine learning and deep learning for intelligent sensing, uncertainty-aware inference, multi-agent systems and autonomous systems. The lab's official site describes work across sensors, algorithms, computing systems and autonomous decision-making, with an emphasis on reliable and resource-aware intelligent systems.

Application deadline: August 22, 2026 at 11:59 p.m. Central Daylight Time (CDT). The application form requires the applicant to sign in to a Google account.

Application process: complete Professor Lee's recruitment form before the stated deadline. This is a lab recruitment or pre-screening form and does not replace any formal UT Dallas graduate admission application required of selected candidates.

Host country/countriesUnited States
Eligible countries/nationalitiesAll nationalities
Study levelPhD / Doctorate
Field of studyComputer Science, Artificial Intelligence, Deep Learning, Machine Learning, Computer Engineering, Electrical Engineering, Autonomous Systems, Edge Computing, Embedded Intelligence, Intelligent Sensing, Multi-Agent Systems, Uncertainty-Aware Inference
Funding typeFully funded
DeadlineAug 22, 2026
Academic year/intake2026/2027 Spring 2027
Application feeNo fee is stated for Professor Lee’s initial Google recruitment form. A separate UT Dallas graduate-application fee may apply if a candidate proceeds to formal admission; check the university portal for the current amount and waiver options.

Benefits

  • A fully funded Ph.D. research position for Spring 2027.
  • Research supervision from Professor Minah Lee in the UT Dallas Department of Electrical and Computer Engineering.
  • Research opportunities in adaptive and intelligent sensing, uncertainty-aware machine learning, embedded intelligence, edge computing, multi-agent autonomy and autonomous decision-making.
  • Access to the SEDIS Lab and UT Dallas engineering research environment.

Funding verification: the announcement describes the openings as fully funded but does not itemise the stipend, tuition waiver, health insurance, fee coverage, duration or summer support. Applicants should obtain the complete funding offer in writing before accepting.

Eligibility summary

  • Prospective full-time Ph.D. students seeking Spring 2027 admission.
  • Strong academic record and preparation relevant to computer science, artificial intelligence, electrical engineering, computer engineering or a closely related discipline.
  • Prior research experience in machine learning or deep learning is strongly encouraged.
  • Research interests aligned with intelligent sensing, uncertainty-aware inference, embedded intelligence, multi-agent systems, autonomous systems or related topics.
  • No nationality restriction is stated in the recruitment announcement; international applicants must satisfy UT Dallas admission, English-language, financial-document and immigration requirements.

The current UT Dallas Electrical Engineering Ph.D. programme page states that applicants should hold a master's degree in electrical engineering or a closely associated discipline and ordinarily have a graduate GPA of 3.5 or better on a 4.0 scale. Applicants from CS or AI backgrounds should confirm programme fit with Professor Lee and the department.

Requirements

  • Submit the linked Spring 2027 SEDIS Lab recruitment form by the deadline.
  • Demonstrate strong academic performance and relevant machine-learning or deep-learning research preparation.
  • Explain research interests and their alignment with Professor Lee's current work.
  • If shortlisted, complete the formal UT Dallas Ph.D. application and all departmental requirements.
  • The current programme page lists three recommendation letters and an admissions essay and says the GRE is temporarily waived; verify the requirements that apply to Spring 2027 before submitting the university application.

Documents required

  • Information and materials requested in Professor Lee's Google recruitment form.
  • Curriculum vitae or résumé highlighting research experience, publications, technical skills and projects.
  • Academic transcripts and degree records.
  • Statement describing research interests and fit with the SEDIS Lab.
  • Three recommendation letters and an admissions essay for the formal Ph.D. application, subject to the current UT Dallas requirements.
  • English-language, identity, financial and immigration documents where applicable.

Language/test requirements

Check provider requirements for language or test requirements.

How to submit applications

Provider: SEDIS Lab, The University of Texas at Dallas

Apply using the linked Google form. Official verification pages: https://ece.utdallas.edu/people/tenure-system-faculty/lee-minah/ | https://academics.utdallas.edu/fact-sheets/ecs/phd-electrical-engineering/

Listing-board disclaimer

Prime Scholarship Alerts is a listing board only and does not provide application procedures or guarantee scholarship awards. Verify all requirements, deadlines, fees, and application instructions through the provider before applying.

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