FPGA Machine Learning Developer (EP-CMG-OS-2025-21-GRAE)

Job Description

Your responsibilities

We are seeking a FPGA & Machine Learning Developer to join the Edge SpAIce project, an EU-funded initiative leveraging CERN technology for onboard image processing with Machine Learning (ML) on FPGAs. The project aims to monitor plastic pollution in the ocean using Earth Observation (EO) satellites equipped with hyperspectral cameras. By performing real-time image segmentation onboard, the system will identify marine debris and send rapid alerts, reducing the need for extensive data transmission.

CERN's hls4ml tool, originally developed for ultra-low latency Neural Network (NN) inference in LHC experiments, will be a key part of the project. The successful candidate will develop and optimize NN inference for NanoXPlore FPGAs, which are well-suited for low-power, high-throughput embedded processing.

Key Responsibilities:

• Develop and optimize Neural Network (NN) inference implementations for NanoXPlore FPGAs.
• Implement image segmentation NNs for real-time onboard identification of marine debris.
• Benchmark and evaluate FPGA demonstrator systems, measuring latency, power efficiency, and accuracy.
• Collaborate with international partners specializing in satellite technology, EO applications, and NN deployment on space hardware.
• Present research findings at CERN and international conferences/workshops.

Read more about the Edge SpAIce project:

https://edgespaice.eu/

https://home.cern/news/news/knowledge-sharing/cerns-edge-ai-data-analysis-techniques- used-detect-marine-plastic 

https://zenodo.org/records/13865939

More information here: https://edgespaice.eu/actors/

Your profile

Skills

• Experience with FPGA development, including High-Level Synthesis (HLS), Hardware Description Languages (HDLs) such as Verilog or VHDL, and C++.
• Familiarity with hls4ml, NanoXPlore FPGAs, and Quantization Aware Training is a plus.
• Understanding of Neural Networks for image processing, particularly image segmentation.
• Knowledge of Earth Observation applications and hyperspectral imaging.
• Strong teamwork and communication skills, with the ability to present and document technical work effectively.

Eligibility criteria:

• You are a national of a CERN Member or Associate Member State.
• By the application deadline, you have a maximum of two years of professional experience since graduation in EE / CS (or a related field) and your highest educational qualification is either a Bachelor's or Master's degree.
• You have never had a CERN fellow or graduate contract before.
• Applicants without University degree are not eligible.
• Applicants with a PhD are not eligible.

Additional Information

Job closing date: 19.03.2025 at 23:59 hrs CET.

Contract duration: 18 months, with a possible extension up to 36 months maximum.

Working hours: 40 hours per week

Target start date: 01-April-2025

Job reference: EP-CMG-OS-2025-21-GRAE

Field of work: Electrical or Electronics Engineering

What we offer

• A monthly stipend ranging between 5196 and 5716 Swiss Francs (net of tax).
• Coverage by CERN's comprehensive health scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.
• Depending on your individual circumstances: installation grant; family, child and infant allowances; payment of travel expenses at the beginning and end of contract.
• 30 days of paid leave per year.
• On-the-job and formal training at CERN as well as in-house language courses for English and/or French.

About us

At CERN, the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature. Find out more on http://home.cern.

Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Employing a diverse workforce is central to our success.