Electrical technical állások Külföldön (programozó, fejlesztő)

• Develop diagnostic and troubleshooting functions to quickly identify root causes and propose correct corrective actions
• Collaborate closely with system and function owners in development projects to ensure strong diagnostic support built in

• Development of firmware for MicroTCA-based motion controller system
• Contributing to system architecture and specifications of firmware modules for scientific data acquisition systems and photon science experiments
• FPGA firmware design using VHDL (for AMD/Xilinx FPGAs)

• Responsible for Emerson DeltaV process control system and bus and third-party systems
• Creation and implementation of comprehensive technical automation concepts (Emerson DeltaV)
• Development of libraries, engineering templates, DeltaV code, graphics, and recipes

- Study current IETF drafts, NIST PQC standards, and prior works integrating Post-quantum cryptography (PQC) into IPsec - Propose and test fragmentation mitigation mechanisms for lossy networks - Extend a selected IPsec stack using open-source PQC libraries - Measure handshake message sizes,...

• Development of tests for safety and mission critical software in the field of helicopter avionics
• Analysis and debugging of software in context of test operations
• Implementation of automated scenarios
• Carrying out formal software acceptance tests including reviews and documentations

We are seeking a Field Applications Engineer (FAE) to support our customers in Central Europe, with a primary focus on MCU hardware and software solutions. The ideal candidate will have a strong technical background in microcontroller technology and a passion for helping customers integrate our...

• Development and maintenance of embedded software components in C/C++
• Porting and rehosting existing software solutions to new target architectures
• Parallelisation of software processes on multi-core processors
• Integration and use of tools such as Tiger Lab for simulation and analysis

• Design and implement end‑to‑end AI pipelines for time‑series and event‑driven sensor data (e.g., pressure, temperature, current, voltage, etc.)
• Combine physical models with data‑driven approaches (hybrid / physics‑informed machine learning) to improve robustness and interpretability