Thesis opportunities- Genetic algorithms for solving machine vision tasks

At SICK, we develop SICK Nova, a software platform and user interface that allows users to configure image processing on cameras to solve industrial applications such as counting, measuring, and quality inspection. However, this configuration process can be challenging for users without extensive knowledge of machine vision.

Genetic algorithms (GAs) are optimization methods inspired by natural selection. They iteratively evaluate candidate solutions and evolve them toward better performance.

Thesis Focus

This thesis explores how genetic algorithms can be applied to automatically configure and optimize machine vision tasks. The envisioned workflow is that a user provides a set of images together with the desired outcomes, and the GA attempts to find a solution through intelligent trial and error.

Research Questions

• How should a GA be designed to effectively solve machine vision tasks?
• Which types of applications benefit most from GA-based optimization?
• How can the evolutionary process be guided to balance efficiency and accuracy?

(Attr: John Stynsberg)

Prerequisites
An interest in or experience with genetic algorithms and machine learning is beneficial.
You may use any programming language you are comfortable with.

Contact

For more information about the position, contact:

John Stynsberg, Software Developer, john.stynsberg@sick.se

or

Sarah Lantz, HR Business Partner, +46 739 10 99 37.

We warmly welcome your application — please submit it no later than October 26th.

SICK is a world-leading supplier of sensors and sensor solutions for industrial applications. We’re part of SICK AG — a global leader in sensor technology with 10,000 employees across 50 countries and headquarters in Freiburg, Germany. Together, we build technology that makes industries more efficient, intelligent, and safe.

As a Machine Vision Innovation Center, SICK Linköping develops high-performance cameras and advanced AI-powered software that drives the future of both manufacturing and logistics automation. Whether it’s helping robots pick the right item or enabling high-precision quality control with 2D and 3D vision, our solutions bring clarity, speed, and smart decision-making to complex industrial environments — all driven by a dedicated team of 100 colleagues.

We are very proud of being a healthy and attractive workplace. We have consistently been recognized as one of the best workplaces in Sweden according to the Great Place to Work survey. We actively work to reduce our climate footprint and engage in various initiatives to contribute to society and enhance diversity at our workplace.