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Write your thesis with us Kick-start your career with us Join us for an internship or summer job
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.
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.
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.
We are always looking for people and we want to know who you are! The first step is to apply!
There are many methods for how to estimate the 6D pose of an object in an rgbd (color and depth) image. Traditional methods have recently met competition from Deep Learning based methods.
Can we overcome the performance of a network pre-trained traditionally on open-source datasets by leveraging self-supervised pre-training on the application images without annotations? Can we improve performance by incorporating images from the same domain, but outside the actual application scope?
Hand-eye alignment is the procedure of establishing a common coordinate system between a robot (industrial or cobot) and a vision sensor.
Deep learning exists in various forms, but one of the most common ways to interpret images is using convolutional neural networks. These are especially prevalent in an embedded setting where computational resources are limited.
This thesis proposes the question, can deflectometry be used as an alternative, or complimentary measurement method when objects are shiny / highly reflective.
The task is to reconstruct the 3D scene based on the series of images. This will give a richer description of the target where more hidden surfaces are exposed and where stereo reconstruction artifacts can be rejected.
Now’s your chance to be part of a new team that’s ready to make an impact on our initiative of building a new generation of camera-based sensors. If you’re a Software Develoer, excited about launching innovative products and eager to embrace new challenges, this could be the opportunity for you.
Now’s your chance to be part of a new team that’s ready to make an impact on our initiative of building a new generation of camera-based sensors. If you’re a Software Architect, excited about launching innovative products and eager to embrace new challenges, this could be the opportunity for you.
Now’s your chance to be part of a new team that’s ready to make an impact on our initiative of building a new generation of camera-based sensors. If you’re a Software Developer, excited about launching innovative products and eager to embrace new challenges, this could be the opportunity for you.
You can always let us know who you are and what you are interested in!
Have a look at the films below for inspiration on topics for a thesis.
Handheld 3D Scanner
Narrow Pretraining of Deep Neural Networks
Deep Learning in 3D Point Clouds
Language Models for Configurable Systems
Photorealistic Simulations of Laser Triangulation System
Hyperspectral Cameras
Deep Learning from Teacher Sensors
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
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