Postdoctoral Researcher

Texas A&M University System • College Station, TX

1d • Onsite

About The Position

The Postdoctoral Researcher will work on research projects in the area of wireless communication system design with machine learning applications. The ideal candidate will have a strong background in wireless communication, signal processing, and machine learning. They should also possess the skills necessary to develop complex models, algorithms, and simulations to improve the performance of wireless communication systems. We offer the opportunity to work with a team of world-class researchers and engineers, competitive salary and benefits, access to state-of-the-art research facilities and resources, and the opportunity to make significant contributions to the field of wireless communication systems and machine learning.

Requirements

• Doctoral degree
• No experience required
• Knowledge of wireless communication protocols and standards.
• Proficiency in programming languages, such as Python, C++, or MATLAB.
• Ability to design and execute complex research projects, and to interpret and communicate the results in a clear and effective manner.
• Excellent written and oral communication skills.
• Ability to work effectively both independently and as part of a team.

Nice To Haves

• Ph.D. in Electrical Engineering, Computer Science, or a related field with a focus on wireless communication and machine learning.
• Proven experience with modeling and simulation of wireless communication systems.
• Strong background in machine learning and artificial intelligence with proficiency in using ML frameworks like TensorFlow or PyTorch.
• Strong publication record in top-tier, peer-reviewed journals and conferences.
• Experience with deep learning applications in the context of wireless communication systems.
• Experience in writing successful grant applications.
• Familiarity with software-defined radio platforms and toolkits.

Responsibilities

• Carry out extensive research and development in wireless communication systems and machine learning. This includes formulating research problems and developing innovative solutions.
• Develop sophisticated models and simulations of wireless communication systems. Validate these models using real-world or synthetic data.
• Apply machine learning algorithms and techniques to improve the efficiency, reliability, and performance of wireless communication systems.
• Conduct comprehensive data analysis to understand the performance of wireless communication systems and their bottlenecks. Apply statistical and machine learning techniques to this data to gain insights.
• Work closely with other researchers and engineers on interdisciplinary projects.
• Prepare research reports, and present findings at conferences, workshops, or other academic or industry events.
• Participate in the preparation and submission of grant applications to fund ongoing and new research.
• Contribute to the supervision of undergraduate and graduate students engaged in research work.
• Performs other duties as assigned.

Benefits

• Competitive medical insurance benefits through Blue Cross and Blue Shield of Texas and Prescription coverage by Express Scripts.
• Options for Vision, Dental, Life, and Long-Term Disability insurance.
• A defined benefit retirement plan with the Teacher Retirement System of Texas (TRS) with 8.25% employer contribution.
• Additional Voluntary Retirement Programs: Tax Deferred Account 403(b) and a Deferred Compensation Program 457(b).
• Flexible spending account options for medical and childcare expenses
• Generous paid time off with holidays, vacation and sick leave.
• Robust free training access through LinkedIn Learning plus professional development opportunities.
• Tuition assistance and Educational release time to further your academic pursuits.
• Access to Engineer Your Wellness programs that provide opportunities for employees to engage in health and fitness.
• Wellness release time offered to employees to promote work/life balance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree