Hiwi - Studentische Hilfskraft (m/w/d) | Institute for Artificial Intelligence | University of [...]

Universität Stuttgart; Stuttgart; Vor Ort; EUR 20.000 - 40.000; Teilzeit

Zusammenfassung

L'Institut d'intelligence artificielle de l'Université de Stuttgart recherche un assistant HiWi pour contribuer à des recherches sur des modèles de substitution neuronaux dans le cadre de l’apprentissage automatique. L'accent est mis sur l'optimisation des générateurs de données pour des équations aux dérivées partielles à l'aide de techniques d'apprentissage actif. Ce poste offre une expérience pratique et la possibilité de poursuivre une thèse.

Leistungen

Expérience pratique en recherche

Possibilité de suivre avec une thèse

Qualifikationen

• Connaissance de Python et des bases de l'apprentissage automatique.
• Idéalement, expérience avec les clusters GPU.
• Doit être dans une phase intermédiaire du programme de licence ou début de programme de master.

Aufgaben

• Étendre la base de code de recherche existante.
• Conduire des expériences sur notre cluster GPU.
• Améliorer l'efficacité des données pour les modèles de solution PDE.

Kenntnisse

Python

Machine Learning

PyTorch

English

German

Ausbildung

Étudiant(e) inscrit(e) à l'Université de Stuttgart

Jobbeschreibung

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Hiwi - Studentische Hilfskraft (m/w/d) | Institute for Artificial Intelligence | University of Stuttgart, Stuttgart

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Client:

Location:

Stuttgart, Germany

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

70fe18b9a3a3

Job Views:

4

Posted:

25.06.2025

Expiry Date:

09.08.2025

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Job Description:

The Machine Learning for Simulation Science group is working on core machine learning research with a focus on graph neural networks and geometric deep learning, the synthesis of discrete (algorithmic) components and continuous learning systems, and the intersection of machine learning and the simulation sciences.

We are looking for a HiWi to help with our research on neural surrogate models for solving partial differential equations (PDEs). PDEs play an essential role in many areas of science and are traditionally solved using numerical solvers, which can be slow and require a lot of computational resources. Thus, the goal is to replace such expensive numerical solvers with fast neural surrogate models. In our current project, we are focusing on improving the data generation phase for the neural PDE solver by using active learning techniques, i.e., by selecting the most informative data points iteratively to increase the data efficiency.

Tasks

Extend our existing research code base by incorporating new modules and algorithms.

Conduct experiments on our GPU cluster.

Proficiency in Python programming

Basic understanding of Machine Learning

Basic knowledge of PyTorch (or another ML framework).

Preferably experience with executing experiments on a GPU cluster

Competency in English or German

Enrolled as a student at the University of Stuttgart

Since we are looking to hire someone long-term, you should have some time in your studies left (i.e., be in the middle stage of a bachelor's program up to the beginning of a master's program)

We offer:

Hands-on experience in machine learning research

Familiarize yourself with the current research trends in ML for Science

Possibility to follow up with a thesis

Up to 40 hours per month contract (initially limited to 6 months, can be extended afterwards)

We are looking forward to your application! We will review them on a rolling basis until the 30.06.24. Please send a short cover letter, transcript, and CV to the contact email informed below.