CURRENT OPEN VACANCIES
Would you like to work from home during this sensitive time of the COVID-19 quarantine? Please apply to any of the vacancies below that you find matches to your skillset! The following vacancies only apply to current students of the University of Twente. Unfortunately, students from Saxion are not able to get a UT Flex job through the ET faculty, of which FEST is part of. There are also external vacancies from our collaborating companies.
Type of work: Master Thesis
- Research into applicable vision deep-learning models for parcel picking.
- Analysis of use-case and requirements through stakeholder involvement.
- Vision-based machine learning background.
- Python and/or C# programming.
Good to have:
Interest in factory automation (i.e. industrial robotics and camera systems).
Brief explanation: This research woul be on the topic of onject detection and instance segmentation networks with the company AWL.
Type of work: MSc Thesis: The goal of the assignment is modeling and controlling a specific system given by the client IMS.
Location: IMS Almelo / Perron 038 Zwolle
Team: IMS Research & Development
- 3D modeling
- Optimization + Machine Learning
- Systems Control
Brief explanation: Automotive lighting systems such as headlights and side-projectors are becoming more intelligent. For example, adaptive beam shaping and high definition has been made possible by technological advances regarding resolution, speed, definition, sharpness, contrast, color of the illumination systems.This increasing complexity leads to new demands for both manufacturing and validation. Both internal product specifications and external regulations demand stringent and extensive functional analysis. Light projection quality analysis is one of the most important aspects therein. Projection quality (PQ) analysis system specifications include total analysis time, compactness, projection angles range, intensity range and resolution, near-field or far-field analysis.
A supervisor from IMS will be attached with the project to provide experience with the setup and support with the thesis. A daily supervisor will also be provided by Fraunhofer Project Center at the University of Twente to support with the theoretical and technical aspects of the thesis. The master thesis will be part of the PRISMA project, a consortium project around Computer Vision applications, to which more information can be provided on request.
Type of work: Part-Time
- Confident with C# in parallel coding and automations
- Basic knowledge of optimization solutions (optional)
Brief explanation: Looking for a creative and motivated student to assist in development of an advanced algorithm through C#. The student will work with a team of engineers in the development of an automated solution.
vision control, Pattern recognition, feature engineering and machine learning
Type of Work: Master Graduation Project
- Data analytics tools
- Pattern recognition
- Feature engineering
- Computer Vision tools
Good to have knowledge in: Machine learning, precision mechanisms and high-tech solutions, Deep Learning, Image filtering and analysis, Coding experience in Python or similar language
Brief explanation: Thesis projects can start in May and will last the standard duration of a master thesis program. During that time, it can be required to have occasional visitations with companies and external expertise teams
Timeline: 4 days a week at the office, 5 th day trainee program.
Type of work: Traineeship
Responsibilities: You will be the central point of communication for the Industry 4.0 program. You will keep the systems up to date, organize project meetings, communicate with project managers, and keep an overview of the progress of the project portfolio. You will be part of the Program Office of ISPT where all the projects are coordinated and report to the Resource Manager.
- Fluent in Dutch.
- A university degree in, for example, Process Technology, Mechanical Engineering, Measurement and Control Engineering, or Information Technology.
- Independent and quick to pick up new information, communicative, proactive, responsible,
Good to have: A demonstrable interest in ICT developments such as machine learning, Internet of Things, and Artificial Intelligence. You want to deepen your knowledge on aspects related to Industry 4.0 e.g. supplier embedding and machine- to-machine negotiation, robotics and mechatronics, predictive modelling, and zero defect manufacturing.
Brief explanation: You organize the communication for projects and results while working in a dynamic environment with other stakeholders.
Contact email@example.com (Leontien Kalverda)
Type of work: Master thesies
Brief description: This Master thesis will be executed at Aeronamic as part of the 3D2SKY project. The goal of the 3D2SKY project is to print certifiable products for Aerospace applications with Laser-Powder Bed Fusion. Within the project, an EOS M290 machine and several other equipment around the printing process have been acquired and are available for experimentation purposes.
Furthermore, Simufact additive suite and Siemens NX are available for simulation purposes. As Aeronamic’s strategy is to have all design and manufacturing engineering capabilities contained in a single software environment, Aeronamic invested in Siemens NX AM CAM to expand the existing Siemens NX CAD/CAM infrastructure.
Additionally, Aeronamic is looking to integrate simulation of print jobs with Simcenter into the Siemens environment. Goal is to investigate Simcenter’s capabilities and to evaluate whether the software is fit for purpose and define gaps. Comparison with print jobs (to be) performed and/or existing simulations performed in Simufact may be part of the investigation.
The intended global structure of the project will be:
- Understanding how the simulation works. Which assumptions are done (e.g. uniform temperature distribution vs. very high local temperatures in reality) that affect the accuracy.
- Select or design test geometries to evaluate residual stress, distortion and warpage
- Compare calculated distortion with measured distortion
- Predict recoater crashes
- Optionally compare Simcenter results with Simufact
- Evaluate algorithms within Simcenter which (iteratively) compensate geometry for distortion