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Write your thesis with us Kick-start your career with us Join us for an internship or summer job 

Write your thesis with us

We offer several thesis projects annually. We announce our theses opportunities during September and we look forward to meeting you at the local Teses fairs in Linköping and Norrköping to tell you more. If you do not find anyting suitable for you but have an idea for a thesis, then you are welcome to contact us and tell us about your idea. Doing your thesis with us is not only developing and fun, but also an excellent way to get a permanent job at SICK Linköping.

Join us for an internship or summer job

At SICK Linköping we find internships and summer jobs to be an excellent way of connecting with talented students for future employment while getting qualified tasks done. We put time and effort in defining suitable assignments, and create excellent conditions for our interns and summer workers, to learn and have fun while working with us! If you are interested in sensor technology, image processing, and machine vision – keep your eyes on our career page during the beginning of the year when we announce our summer job opportunities! If you are looking for an internship, get in touch with us to share your interests. We have opportunities within several areas that might be just the right one for you.

Kick start your career with us

Are you eager to practice what you have learnt and do you have some hours to spare on a weekly basis? Then there might be a suitable opportunity for you to join us for a part-time job. Especially if you have programming skills and share our passion for sensor technology, image processing, and machine vision. Get in touch with us to share your interests and talk about possible opportunities.

Unlock your full potential and join us in creating a smarter world!

We are always looking for people and we want to know who you are! The first step is to apply!

Job title
Job category
Location
Apply by
Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Investigate lightweight pruning methods for neural networks that can run on embedded devices. Explore suitable backbone architectures and evaluate open-source tools through literature review and hands-on experimentation.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Curious about how AI can support users without taking center stage? This thesis explores subtle, context-aware ways to integrate AI into industrial interfaces – enhancing usability while keeping the experience intuitive and familiar.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Curious about how AI can simplify and enhance machine vision? Join us at SICK Linköping and explore how intelligent systems can recommend tools based on images and user prompts. A unique chance to work with real-world impact and cutting-edge tech.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Explore how to train instance segmentation networks using only global class labels. This thesis investigates efficient learning methods to reduce annotation effort while customizing models for new tasks.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Explore how large language models can act as reasoning agents to solve machine vision tasks. This thesis investigates model design, application types, and how to represent camera data for intelligent automation.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Investigate how inverse rendering can be used to detect surface defects from 2D images. This thesis explores the benefits and limitations of estimating 3D scene properties for industrial inspection tasks.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Explore error sources in hand-eye alignment for robot guidance. This thesis investigates how different factors affect object localization accuracy and aims to develop methods to identify and visualize their individual contributions.

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

In machine learning, support vector machines (SVM) are a well-proven family of algorithms for binary classification. The heart of the algorithm is linear regression with a particular loss function, the so-called margin loss. Support vector regression (SVR) is a closely related algorithm for regression problems that uses a loss function often referred to as epsilon-insensitive loss.

We believe that some problems might benefit from combining these two types of loss functions. Similar ideas have been published before (https://arxiv.org/abs/1106.3397), but have not been thoroughly studied, and is therefore not readily available in software packages.

During this project you would implement such an algorithm, either within an existing framework (e.g. liblinear, pytorch, scikit-learn) or from scratch, and analyze how it performs compared to existing algorithms.

Depending on your interests, there are also ideas for additional modifications to investigate, and some parallels to neural network design that you could explore. We look forward to discussing details at the interview.

Prerequisites

You should have an interest in algorithms and familiarity with mathematical optimization and/or machine learning, including some related programming experience.

Hybrid loss functions for support vector regression

Contact
For more information about the position, contact:

Erik Hedberg, Algorithm Developer, erik.hedberg@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.   

Job category: Opportunities for students
Location: Linköping
Apply by: 2025-10-26

Explore how genetic algorithms can be used to automatically configure machine vision tasks. This thesis combines optimization techniques with image-based problem solving to improve usability and performance.

Job category: Software Development
Location: Linköping
Apply by: 2025-10-26

Join SICK Linköping and shape the future of industrial automation! As an FPGA Developer, you'll work with cutting-edge 3D vision technology in a passionate, collaborative team. Dive into high-speed image processing and make a real impact—curious? Learn more!

Job category: Product Marketing
Location: Linköping
Apply by: 2025-10-12

Shape the future of machine vision! At SICK Linköping, you'll lead the product strategy for our 3D Vision portfolio in a global, innovative environment. Join a passionate team where technology, sustainability, and workplace wellbeing are top priorities.

Can't find what you're looking for?

You can always let us know who you are and what you are interested in!

Examples of previous thesis opportunities

Have a look at the films below for inspiration on topics for a thesis.

Mattias Johannesson

Handheld 3D Scanner

Daniel Rydström

Narrow Pretraining of Deep Neural Networks

Sofia Nilsson

Deep Learning in 3D Point Clouds

John Stynsberg

Language Models for Configurable Systems

Jens Edhammer

Photorealistic Simulations of Laser Triangulation System

Fredik Löfgren

Hyperspectral Cameras

Andreas Wrangsjö

Deep Learning from Teacher Sensors

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Contact us

We are the People and Culture team at SICK Linköping. We can answer all your question on recruitment, life at SICK Linköping, student opportunities and much more.

Charlotte Axelsson
charlotte.axelsson@sick.se
+46 739 2099 50

Sarah Lantz
sarah.lantz@sick.se
+46 739 10 99 37