Job Description
Postdoctoral Fellow
Department of Computer Science
All Applicants
40
Exempt
Jun 01, 2024
Expected to Continue Until Mar 01, 2027
AUSTIN, TX
Must be eligible to work in the United States on a full-time basis for any employer. Position expected to continue until March 1, 2027.
Deadline for Application: Applications will be reviewed continuously until the position is filled.
Contact Information:
. Please note only applications through Workday will be considered.
Project Affiliation: Army Contract for AI-Driven Network Optimization
About the Project: This exciting opportunity at the University of Texas at Austin involves working on a cutting-edge AI networking project under the guidance of Professor Chandrajit Bajaj. The project focuses on developing Predictive Intelligent Networking (PIN) agents, employing advanced AI techniques for rapid response decision-making in predictive intelligent communication networks. Our innovative approach centers on enhancing network efficiency, reducing overhead traffic, automating PACE communications planning, and improving scalability in challenging environments. Our project is dedicated to crafting advanced machine-learning algorithms specifically designed for network optimization and security challenges. Through rigorous real-world simulation scenarios, we aim to deliver robust solutions that excel in environments with incomplete or uncertain data. This role offers the chance to be part of a pioneering effort to create generic solutions for heterogeneous Army networks, working within the confines of existing network protocols.
-
A dynamic and collaborative research environment at the University of Texas at Austin.
-
Opportunities to work on pioneering technologies in AI and network security.
-
Access to state-of-the-art facilities and resources at the Computer Visualization Lab.
- A chance to contribute to a project with a significant impact in the field of C5ISR communications.
-
100% employer-paid basic medical coverage
-
Retirement contributions
-
Paid vacation and sick time
-
Paid holidays
to learn more about the total benefits offered.
-
Collaborate in the conceptualization and development of theoretical frameworks to underpin AI-driven network optimization.
-
Engage in the design and iterative refinement of AI agents with a special focus on traffic prioritization and network adaptability.
-
Play a pivotal role in controlled scenario testing, contributing to rigorous result analysis and validation.
-
Support the research team by assisting in the preparation of detailed technical reports and presentations that demonstrate project milestones and insights.
-
Ph.D. in Computer Science, AI, Networking, or a related discipline within the last 3 years
-
Solid experience with AI/machine learning methodologies, particularly those applicable to network optimization.
-
Proven ability in programming and familiarity with network simulation tools and environments.
-
A strong propensity for innovative thinking coupled with a disciplined approach to research and collaboration.
-
Publications or significant contributions to the field of AI, machine learning, or networking.
-
Experience with interdisciplinary research and collaborative projects.
-
Familiarity with military or defense communication systems is a plus.
-
Standard office conditions
-
Letter of Interest
-
Research Statement
-
Resume/CV
- Arrange at least three (3) confidential reference letters be sent to
-
Proof of Ph.D. in Computer Science, AI, Networking or a related discipline earned within the last three years.
Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.
, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.
-
E-Verify Poster (English)
[PDF]
-
E-Verify Poster (Spanish)
[PDF]
-
Right To Work Poster (English)
[PDF]
-
Right To Work Poster (Spanish)
[PDF]
.
or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.
EWJP2