Without Professional Experience | Students

Fbh Berlin; Berlin; On-site; EUR 32,000 - 52,000; Full time

Benefits offered by this job

Open international team

Modern Berlin Adlershof workplace

Valuable experience

Job summary

The Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik (FBH) RF Power Lab is seeking a master student to evaluate behavioral models for a dual input dual output supply voltage modulated system. You will gather data, parameterize models across temperatures and apply ML to predict parameter dependencies.

Collaborate on ML-based control of PA performance, train models from experimental data, and verify results.

Qualifications

• On-going master studies in relevant fields (Computer Science / Electrical Engineering / Physics with Applied Mathematics).
• Knowledge of machine learning, signal processing, microwave engineering, nonlinear and behavioral modeling, AI-based modeling.
• Interest in applied mathematics and signal processing.
• Experience in Matlab and Python.

Responsibilities

• Evaluate a novel behavioral model for a supply voltage modulated DIDO system across wide temperature variation.
• Develop ML models for parameter dependence and verify against experimental data.
• Control and optimize PA performance under temperature variations using ML models; verify with experimental data.

Skills

Machine learning

Signal processing

Microwave engineering

Nonlinear modeling

Behavioral modeling

AI-based modeling

MATLAB

Python

Education

On-going Master in Computer Science / Electrical Engineering / Physics with Applied Mathematics

Master-level studies in a related field

Tools

MATLAB

Python

Job description

The Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik (FBH) is an application-oriented research institute in the fields of high-frequency electronics, photonics and quantum physics. It researches and realizes electronic and optical components, modules and systems based on compound semiconductors. These devices are key enablers that address the needs of today’s society in fields like communication, energy, health, and mobility.

The focus in the RF Power Lab is on applications with output powers in the range of 5...200 W in the microwave range up to 40 GHz. We work on novel concepts to increase efficiency in broadband modulated power amplifier systems for modern telecommunication and signals with high peak-to-average power ratios. In particular, we investigate dual-input amplifier systems based on load & supply-voltage modulation and how to use them in AI-controlled intelligent self-tunable systems. Integrated reconfigurable components and circuits are also in focus and more advanced integrated transceivers for radar and telecom. In addition, we develop novel autonomous RF measurement systems for improved RF power transistor characterization and the optimization of such devices based on machine learning.

Reference number 07/26

Your tasks (with focus depending on backround)

1. Evaluation of a novel behavioral model for a supply voltage modulated dual input dual output (DIDO) system over large temperature variation

• Acquiring experimental data for the ET PA at different temperatures T1, T2, …
• Identify model parameter for a recently developed DIDO model for each temperature
• Use machine learning (ML) to create a model for the parameter dependence
• Verify the model for experimental data

2.Control and optimization of PA performance for temperature variations

• Develop a ML model for control of the DIDO
• Train the ML model based on the behavioral model in task 1
• Verify the ML model based on experimental data

Your profile

• On-going master studies in Computer Science. Electrical Engineering, Communications and Signal Processing, or Physics with Applied Mathematics
• Knowledge of machine learning, signal processing, microwave engineering, nonlinear and behavioral modeling, AI-based modeling
• Interest in applied mathematics, signal processing
• Experience in Matlab and Python (preferably)
• Starting date: a.s.a.p.

Our offer

• an open and appreciative international team, always available with help and advice
• a modern workplace in Berlin Adlershof with good public transport connections
• exciting insights into practical applications and the opportunity to gain valuable experience

If you have questions, please contact Dr. Olof Bengtsson, Tel.: [phone], E-Mail: [e-mail].

Data protection notice: The above contact details are provided exclusively for interested applicants to get in touch. Enquiries from recruitment agencies are not welcome. Any use of the personal information contained in this advertisement by other third parties is expressly prohibited.