15 meilleures offres (algorithm engineer, belgium) (à pourvoir)

master thesis or bachelor thesis
Vintecc —Roulers
- Informatique
- Master
- C++
Backend Developer
Hysopt —Deurne
- Temps plein
- Travail hybride
- Informatique
- Informatique
- Anglais
Postuler rapidement
Integration Specialist - MuleSoft/Boomi
Deloitte —Zaventem
- Temps partiel
- Microsoft Powerpoint
- Microsoft Word
- Informatique
Biomedical Research internship
Materialise —Louvain
- Informatique
- Doctorat
- Informatique
Software & AI Solutions Architect
VITO —Mol
- Temps plein
- Travail hybride
- Informatique
- Azure
- Informatique
Postuler rapidement
il y a 3 jours
Project lead - Earth Observation platforms
VITO —Mol
- Temps plein
- Travail hybride
- Informatique
- Doctorat
- Informatique
Postuler rapidement
Marketing AI Product Owner
Telenet —Malines
- Temps plein
- Travail hybride
- Anglais
- Bureau
- Master
il y a 5 jours
Senior Consultant in Data science
Sia —Anvers
- Temps plein
- Travail hybride
- Master
- Machine learning
- IT
Postuler rapidement
FPGA Engineer
Aerospacelab —Belgique
- Temps plein
- Doctorat
- Master
- Développement logiciel
Research Engineer (C++ & Python)
CluePoints —Belgique
- Recherche
- C++
- Machine learning
il y a 3 jours
Machine Learning Engineer (MLOps focus)
Yechte Consulting —Belgique
- Azure
- DevOps
- SQL
Internship Telecommunication Engineer
Aerospacelab —Belgique
- Temps plein
- Master
- Développement logiciel
- Stage
SDR/DSP Engineer
Aerospacelab —Belgique
- Doctorat
- Master
- Scripting
Satellite Verification & Validation Engineer - Mission leading & Test Scripting
Aerospacelab —Belgique
- Temps plein
- Doctorat
- Master
- Bachelier
Network Software Engineer
Aerospacelab —Belgique
- Doctorat
- Master
- JavaScript

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master thesis or bachelor thesis

Vintecc
Roulers

Soumettre votre candidature

Détails de l'emploi

Qualifications

CI/CD
Informatique
MATLAB
Vision par ordinateur
R
Master
C++
C
Bachelier
Deep learning
Simulink
Développement logiciel
Python

Description complète du poste

Are you a student and keen to gain practical experience in an innovative environment?
As a job student at Vintecc, you will work on r eal projects and discover how software, AI and engineering come together to make companies smarter and more efficient. A perfect opportunity to gain knowledge, expand your network and prepare yourself for your professional career.

What to expect:
✔ Practical experience in a high-tech environment
✔ A cool and instructive work experience
✔ A team open to your ideas
Do you have a topic in mind or are you curious about our proposals?
Get in touch and we will be happy to discuss!
You can find some approved topics below: COMPUTER VISION
Profile/required skills
Education: computer science student industrial engineer or computer science student.
Be proficient in the Python programming language (and have experience with C/C++).
Background knowledge about computer vision and practical experience with deep learning. Apply below! SIMULATION/DIGITAL TWINS
Tuning of physical parameters
Goals
The aim of this thesis is to investigate and develop best practices for tuning a virtual physical simulation to an existing ‘counterpart’. Ideally, this will result in a methodology for addressing tuning and various methods for (potentially) automating parts of this task (auto-tuning).
Profile / skills required
Electromechanics / Mechanics / Control & Automation/...System identification / Control engineering / Modelling / Mechatronics/...Basic skills in programming and software development MECHATRONICS & CONTROLS
Scalable Test Framework for Matlab/Simulink Models
In the development of autonomous systems using Matlab/Simulink , reusable libraries are often employed to enhance efficiency. These libraries contain essential functions such as motion control and sensor processing but quickly grow in complexity. To ensure stability and seamless integration into projects, a robust and scalable test framework is essential.
This thesis focuses on developing a flexible test framework that enables efficient verification of library functions.

Key objectives include:
Establishing a scalable test environment in Matlab/Simulink.
Automating tests using Functional Mock-up Units (FMUs) to accelerate simulations and enable execution independent of Matlab.
Facilitating efficient test expansion for future developments and evolving requirements.
This project lays the foundation for a sustainable and reusable testing process , ensuring the long-term reliability and stability of Matlab/Simulink libraries.
Acceleration of Simulations with Reduced Order Modelling
Context
In model-based software development, physical systems are simulated to test control software. However, high-fidelity simulations require significant computational power and time. This thesis explores how Reduced Order Modelling (ROM) and Physics-Informed Neural Networks (PINN) can increase simulation speed without significant loss of accuracy.
Objectives
Accelerate automated testing in CI/CD by replacing computationally intensive models with efficient surrogate models.
Identify bottlenecks in simulation time.
Explore ROM and data-driven techniques for physical models.
Evaluate the trade-off between computational speed and accuracy.
Methodology
A literature study will analyse existing ROM and PINN techniques. Subsequently, several Simulink models will be selected to test suitable ROM methods. The accuracy and speed of the surrogate models will be evaluated in different test scenarios.
Result
A demonstration of ROM and PINN, with a comparative analysis of accuracy and computational efficiency for physical simulations.

Trajectory Optimization for Yarn Tension Control in Composite Material Weaving
Context
When weaving high-tech composite fabrics, weft yarns such as carbon or glass fibers must remain free of twists or kinks. This is achieved by actively regulating yarn tension using a buffer arm positioned between the bobbin and the loom. The bobbin unwinds the yarn at a constant speed, while the buffer arm adjusts the required yarn length to maintain stable tension.
After each cycle, the buffer curve is updated, determining how much yarn needs to be buffered. A feedforward curve for the buffer arm is then generated. Issues arise when the buffer arm needs to buffer more yarn than physically possible or too little. In these cases, the bobbin speed must be adjusted, leading to high torque peaks that negatively impact both the weaving process and the motors.
Objective
This thesis aims to develop a real-time algorithm that optimally combines the feedforward curves of both the buffer arm and the bobbin based on the buffer curve. The goal is to minimize acceleration and torque peaks while ensuring all weaving constraints are met.
Methodology
Analysis Phase: Study of the current algorithm and literature review of state-of-the-art optimization techniques that address similar challenges.
Implementation Phase: Development, testing, and validation of the algorithm using real data. If successful and time permits, integration into the machine software and testing on the actual machine will follow.

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algorithm engineer emplois - belgium

master thesis or bachelor thesis

Backend Developer

Integration Specialist - MuleSoft/Boomi

Biomedical Research internship

Software & AI Solutions Architect

Project lead - Earth Observation platforms

Marketing AI Product Owner

Senior Consultant in Data science

FPGA Engineer

Research Engineer (C++ & Python)

Machine Learning Engineer (MLOps focus)

Internship Telecommunication Engineer

SDR/DSP Engineer

Satellite Verification & Validation Engineer - Mission leading & Test Scripting

Network Software Engineer

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : algorithm engineer (belgium)

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