Real-Time GNSS DSP Engineer (Python/C++)

University of Texas; United States; On-site; USD 104,000 - 174,000; Full time

Benefits offered by this job

Restaurant and lab facilities

Job summary

The University of Texas at Austin's Applied Research Laboratories seeks a DSP Engineering Scientist focused on GNSS to implement and optimize real-time signal processing algorithms on target platforms. The role emphasizes translating theory into efficient software, collaborating with hardware teams, and maintaining reusable DSP components, with a strong emphasis on reliability and performance.

Applicants should have a strong background in DSP, strong coding skills in Python/C/C++, and experience

Qualifications

• Bachelor’s degree in engineering, computer or information science, or related applied sciences.
• Three years of experience in digital signal processing or related field.
• Strong foundation in signal processing theory.
• Proficiency in Python or C/C++ for algorithm implementation.
• Understanding of real-time processing constraints and optimization techniques.
• Knowledge of spectral analysis, transforms, and common filter designs.

Responsibilities

• Design and develop GNSS signal processing algorithms including acquisition, tracking, correlation, and demodulation.
• Translate mathematical models into efficient software implementations and optimize for performance.
• Implement DSP algorithms in Python, C, or C++ for real-time platforms.
• Develop reusable signal processing libraries and perform code reviews.
• Collaborate with hardware teams to integrate DSP components.

Skills

GNSS signal processing

Real-time processing

Python

C

C++

Algorithm design

Analytical skills

Communication skills

Education

Bachelor's degree in engineering, computer or information science, or other applied sciences

Tools

Python

C

C++

Job description

The University of Texas at Austin's Applied Research Laboratories seeks a DSP Engineering Scientist focused on GNSS to implement and optimize real-time signal processing algorithms on target platforms. The role emphasizes translating theory into efficient software, collaborating with hardware teams, and maintaining reusable DSP components, with a strong emphasis on reliability and performance.

Applicants should have a strong background in DSP, strong coding skills in Python/C/C++, and experience