GNSS DSP Research Associate — Innovate GPS Tech

The University of Texas at Austin; Austin (TX); On-site; USD 120,000 - 165,000; Full time

Job summary

The University of Texas at Austin’s Applied Research Laboratories invites applications for a GNSS Digital Signal Processing Research Associate on the Pickle Research Campus. The successful candidate will conduct high-level DSP research for GNSS and RF applications, collaborating with SGL and publishing results.

Candidates must hold a PhD in physics, engineering or related field, and have experience in C++ or Python, with publications and presentations.

Qualifications

• PhD in physics, engineering, other applied science(s).
• Experience developing software in C++ or Python for scientific computing applications.
• One or more years post-graduate experience developing statistical and computational algorithms.
• Demonstrated record of authoring peer-reviewed scientific publications.
• Demonstrated record of presenting scientific content to technical and non-technical audiences.

Responsibilities

• Perform high-level independent digital signal processing research relevant to the interests of SGL.
• Present and publish your research, both internally and externally, including project reviews and technical interfaces with sponsors and external organizations.
• Implement software algorithms in C++ and Python in a collaborative environment and define interfaces between components.
• Provide guidance and assistance to other full-time and student employees.
• Provide technical leadership and identify new directions for research.
• Occasional travel to support meetings.

Skills

C++

Python

Algorithms

Scientific computing

Education

PhD in physics, engineering, or applied science

Tools

Linux

Git

GitHub

Job description

The University of Texas at Austin’s Applied Research Laboratories invites applications for a GNSS Digital Signal Processing Research Associate on the Pickle Research Campus. The successful candidate will conduct high-level DSP research for GNSS and RF applications, collaborating with SGL and publishing results.

Candidates must hold a PhD in physics, engineering or related field, and have experience in C++ or Python, with publications and presentations.