Senior Signal Processing & RF Systems Engineer

The Pennsylvania State University

University Park (TX)

Presencial

USD 140.000 - 266.000

Jornada completa

14 días+
Generador de candidaturas

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Ventajas ofrecidas por este puesto de trabajo

75% tuition discount

Descripción de la vacante

The Pennsylvania State University’s Applied Research Laboratory (ARL) in State College, PA seeks analytical engineers with signal processing expertise to join the Strategic Systems Operation Division. The role focuses on research, design, development, integration, and testing of advanced signal processing and communications systems, with on-site work and limited hybrid options.

Ideal candidates will have strong background in Kalman/Wiener/LMS adaptive processing and experience converting

Formación

  • Bachelor's degree in engineering or science.
  • Experience with signal processing and communications.
  • Knowledge of Kalman/Wiener/LMS adaptive processing.
  • Experience in software design and implementation (C/C++, MATLAB, Python).
  • Familiarity with OSI/UDP/TCP/IP and wireless standards.

Responsabilidades

  • Develop and test signal processing and communications systems.
  • Collaborate with sponsors, engineers, and researchers on projects.
  • Provide updates on program status at meetings.
  • Ensure on-time completion and technical excellence.

Conocimientos

Signal processing
Beamforming
Geolocation
Adaptive filtering
RF signals
MATLAB
Python
C/C++
OSI/TCP/IP
Wireless 4G/5G

Educación

Electrical Engineering
Computer Science
Computer Engineering

Herramientas

MATLAB
Python
C/C++
SDR IQ processing

Descripción del empleo

The Pennsylvania State University’s Applied Research Laboratory (ARL) in State College, PA seeks analytical engineers with signal processing expertise to join the Strategic Systems Operation Division. The role focuses on research, design, development, integration, and testing of advanced signal processing and communications systems, with on-site work and limited hybrid options.

Ideal candidates will have strong background in Kalman/Wiener/LMS adaptive processing and experience converting

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