Maritime SONAR Signal Processing & Automation Engineer

The University of Texas at Austin; Austin (TX); On-site; USD 88,500 - 120,000; Full time

Benefits offered by this job

100% employer-paid basic medical

Retirement contributions

Paid vacation and sick time

Paid holidays

Job summary

The University of Texas at Austin's Applied Research Laboratories seeks a Maritime Surveillance Signal Processing and Automation Engineer (ESA) to develop novel SONAR signal processing and automation solutions. You will implement research-grade software in MATLAB and Python, analyze acoustic data, and supervise junior personnel in a collaborative team.

Applicants should have a Bachelor's degree (Master's preferred) in engineering, physics, or CS, with experience in signal processing, ML, and

Qualifications

• Bachelor’s degree in engineering, physics, computer science, or related technical field.
• Experience developing in MATLAB, Python, and/or similar languages.
• Experience in acoustic data analysis, signal processing, and/or machine learning.
• Experience preparing briefing materials, documentation, and managing schedules.
• Highly organized with ability to plan and coordinate multiple tasks.
• Strong attention to detail, problem solving, and communication skills.

Responsibilities

• Conduct acoustic and system engineering to test and evaluate SONAR signal processing and automation algorithms."],
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Skills

MATLAB

Python

Signal processing

Machine learning

Documentation

Time management

Education

Bachelor’s degree in engineering/physics/computer science

Master’s degree (preferred)

Tools

MATLAB

Python

Job description

The University of Texas at Austin's Applied Research Laboratories seeks a Maritime Surveillance Signal Processing and Automation Engineer (ESA) to develop novel SONAR signal processing and automation solutions. You will implement research-grade software in MATLAB and Python, analyze acoustic data, and supervise junior personnel in a collaborative team.

Applicants should have a Bachelor's degree (Master's preferred) in engineering, physics, or CS, with experience in signal processing, ML, and