Simulation and Machine Learning Engineer (d / f / m)

Henkel; Düsseldorf; Vor Ort; EUR 50.000 - 80.000; Vollzeit

Zusammenfassung

Ein zukunftsorientiertes Unternehmen sucht einen Simulation und Machine Learning Engineer, um innovative Lösungen im Bereich Klebstoffe zu entwickeln. In dieser spannenden Rolle führen Sie Projekte zur Simulation und Modellierung durch, automatisieren die Materialkartenerstellung mit modernen Methoden des maschinellen Lernens und entwickeln geeignete Modelle zur Vorhersage des Klebstoffverhaltens. Sie arbeiten eng mit internen und externen Kunden zusammen, um deren Bedürfnisse zu verstehen und sicherzustellen, dass die Modelle für den vorgesehenen Einsatz geeignet sind. Wenn Sie eine Leidenschaft für Technologie und Innovation haben, ist dies die perfekte Gelegenheit für Sie.

Qualifikationen

• Führung von Projekten zur Simulation und Modellierung von Klebstoffen.
• Automatisierung und Optimierung der Erstellung von Materialkarten.

Aufgaben

• Entwicklung und Bewertung geeigneter Methoden des maschinellen Lernens zur Vorhersage des Klebstoffverhaltens.
• Engagement mit internen und externen Kunden zur Sicherstellung der Modellverwendbarkeit.

Kenntnisse

Maschinenbau

Physik

Computational Science

Python

Maschinelles Lernen

Datenstatistik

Ansys Fluent

Abaqus

Ausbildung

Masterabschluss in Maschinenbau

Masterabschluss in Physik

Masterabschluss in Computational Science

Tools

CFD-Modelle

FEA-Modelle

Jobbeschreibung

Simulation and Machine Learning Engineer (d / f / m)

At Henkel, you can build on a strong legacy and leading positions in both industrial and consumer businesses to reimagine and improve life every day. If you love challenging the status quo, join our community of over 47,000 pioneers around the globe. Our teams at Henkel Adhesive Technologies help to transform entire industries and provide our customers with a competitive advantage through adhesives, sealants, and functional coatings. With our trusted brands, our cutting-edge technologies, and our disruptive solutions, you will have countless opportunities to explore new paths and develop your skills. Grow within our future-led businesses, our diverse and vibrant culture and find a place where you simply belong. All to leave your mark for more sustainable growth.

Dare to make an impact?

YOUR ROLE

• Lead projects related to simulation and modelling of adhesive.
• Automate and optimize material cards creation using modern methods of machine learning and data-based modelling.
• Develop and evaluate suitable machine learning methods to predict adhesive behavior.
• Develop CFD and FEA models for electronic applications with a focus on reliability.
• Predict the application behavior of adhesives (e.g., underfill) and the lifetime of bonded electronic components (e.g., fracture mechanic analysis).
• Develop material models based on experimental data and validate simulation results.
• Engage with internal and external customers, understand and respond to their needs, and ensure that the model is fit for its intended use.

YOUR SKILLS

• Master's degree in Mechanical Engineering, Physics, Computational Science, Mechanics, or similar.
• Advanced knowledge in programming languages for machine learning (e.g., Python).
• Experience in machine learning, artificial intelligence, data statistics, or statistical methods.
• Advanced experience in the behavior, characterization, and modeling of materials (e.g., non-linearity in materials).
• Software knowledge in standard modeling tools, e.g., Ansys Fluent, Abaqus.
• An innovative spirit, enjoyment of learning, and the ability to inspire your customers and colleagues.
• Strong analytical and problem-solving skills.
• Excellent communication skills in English to coordinate with various stakeholders.

At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We welcome all applications across different genders, origins, cultures, religions, sexual orientations, disabilities, and generations.

JOB ID : 24072203

Contract & Job type : Regular - Full Time

Contact information for application-related questions :

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