18. February 2021
PROFACTOR: Master Thesis - Machine Learning for Zero Defect Manufacturing
Machine learning and artificial intelligence are the key elements for achieving zero defect manufacturing goals. In this regard and as a member of zero defect manufacturing platform (ZDMP) initiative, the machine vision group at Profactor is looking for a master's degree student to perform his/her thesis in the field of defect detection using machine vision and machine learning.
The aim is, using a data set of images, to perform detection of defective samples and localization of defects using machine learning methods, specifically deep learning. The candidate will develop algorithms based on convolutional neural networks and attention mechanism to achieve the goals.
- Literature review of existing and state of the art machine learning based defect detection and localization
- Development of algorithms and implementation of the state of the art networks, training and testing the models.
- Integration of the algorithms inside the ZDMP platform
- Documentation in the form of reports and a publication ready document
We are looking for
- Knowledge in machine learning
- Familiarity with one of the deep neural network frameworks (e.g. tensorflow/keras, pytorch)
- Experience in python programming language
- Knowledge in machine vision and convolutional neural networks is an advantage.
- Flexible working hours
- Parking places
- Health measures
- Employee events
- Sport events
Now / 6 months
PROFACTOR's research improves the competiveness of European Industry. We are pioneers of the thinking production. We bring production back home.
We offer for master thesis a compensation of min. 465 EUR per month.
Questions? please contact:
Dr. Amirreza Baghbanpourasl , email@example.com, +43 7252 885 263
You will find further details in the master project description.
Dr. Amirreza Baghbanpourasl
Im Stadtgut A2
Phone: +43 7252 885 263