Edge Data Acquisition and System Characterization Computing

Edge Data Acquisition and System Characterization for Real-Time Computing

Master internship - Leuven | More than two weeks ago

Quantifying How Data Moves, Scales, and Performs at the Edge

At imec, the System Software team develops applications that rely on real-time data processing on advanced edge computing platforms. These systems ingest high-rate data streams from sensors such as cameras, radars and lidars where efficient data acquisition is critical for overall system performance.

In this internship, you will focus on characterizing how efficiently data can be ingested, transported, and prepared for real-time processing in edge systems. You will design and implement a benchmarking framework to evaluate data acquisition pipelines under different conditions.

• Measure key performance parameters such as throughput, latency, CPU utilization, memory usage, and energy consumption
• Analyze buffering strategies, data transfer mechanisms, and hardware interfaces (e.g., CSI, USB, Ethernet)
• Investigate trade-offs between latency, data loss, performance, and energy efficiency
• Evaluate system behavior under varying workloads and multi-sensor configurations
• Use profiling and measurement tools on real platforms (e.g., NVIDIA Jetson, Intel NUC)

• A reusable benchmarking framework for data acquisition in edge systems
• A clear characterization of performance trade-offs
• Concrete recommendations to optimize data acquisition pipelines for real-time applications

imec is a world-leading research and innovation hub in nanoelectronics and digital technologies. In the Innovative Systems and Software Applications (ISSA) department, you will collaborate with experts in software engineering who build the tools and applications that bring imec's hardware innovations to life. You will work in the System Software team within the Software Development & Prototyping (SDP) group, embedded in a team of experienced developers working on real‑world edge computing and embedded systems projects spanning high-throughput sensing, real-time data acquisition, and performance‑critical software.

We offer a stimulating environment at the intersection of AI and embedded systems, hands‑on experience with edge computing systems, and the opportunity to build something that directly impacts how we characterize high-performance systems.

• MSc student in Computer Science, Electrical Engineering, Embedded Systems, or related field
• Available for 3 months (share your available period in the application)
• Strong programming skills in Python and/or C/C++
• Interest in system performance, embedded systems, or edge computing
• Comfortable working with Linux-based environments
• Analytical mindset and interest in measurement and experimentation
• Eager to learn, take initiative, and deliver tangible results
• Strong communication skills and ability to work independently
• Good written and verbal English skills
  
  Experience with edge devices (e.g., Jetson), data acquisition or benchmarking is a plus

Type of internship
:
Master internship

Duration
: 3 months

Required educational background
:
Computer Science, Electrotechnics/Electrical Engineering

Supervising scientist
:
Cagatay Ozdemir ()

Reference code
: 2026-INT-185 (mention in your application)

Imec allowance will be provided.

Applications should include the following information:

• Resume
• Motivation
• Current study