Praktikum "entwicklung Eines Simulators Zur Bestimmung Abgestrahlter Noise Power Ratio Bei Phased Array Antennen" (d/m/w)
AIRBUS DS GEO SA
Attractive compensation; not specified; flexible 3...
Flexible work hours based on a 35-hour work week.
Python programming skills
Electrical engineering student status
Understanding of electromagnetic waves
This internship at AIRBUS DS GEO SA focuses on developing a simulator for determining the Noise Power Ratio (NPR) in phased array antennas, essential for satellite communication. Ideal candidates are enrolled students in relevant fields such as electrical engineering or software engineering with a strong interest in high-frequency technology and programming skills, particularly in Python
Job Summary
The role involves developing a Python-based simulator to quantify Noise Power Ratio improvements in phased array antennas for satellite constellations.
Candidates will receive mentorship from experienced employees and gain valuable insights into the spaceflight industry.
The position offers flexible working hours based on a 35-hour work week with attractive compensation.
Matching Summary
Match Score: 75
This internship at AIRBUS DS GEO SA focuses on developing a simulator for determining the Noise Power Ratio (NPR) in phased array antennas, essential for satellite communication. Ideal candidates are enrolled students in relevant fields such as electrical engineering or software engineering with a strong interest in high-frequency technology and programming skills, particularly in Python.
Salary
Attractive compensation; Not specified; Flexible 35-hour work week
Skills & Requirements
Must-have
Python programming skills
Electrical Engineering student status
Understanding of electromagnetic waves
Nice-to-have
Object-oriented programming knowledge
High-frequency technology theory background
Interest in spaceflight industry
Key Requirements
Currently enrolled student in Electrical or High-Frequency Engineering
Software Engineering or Computer Science degree preferred
Knowledge of object-oriented programming in Python