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Digital Twin, Data and Process Modeling Specialist (d/f/m)

Employer
Henkel
Location
Düsseldorf, Germany
Salary
Competitive
Closing date
Sep 9, 2022

View more

Discipline
Physical Sciences, Information Technology, Other, Manufacturing/QA/QC
Position Type
Full Time
Job Type
Other
Organization Type
Other Corporate

Job Details

At Henkel, you can be a game changer and craft your career. Unleash your entrepreneurial spirit by bringing your ideas to life within a global team. Our leading brands and technologies, along with our high-performing businesses will provide you with countless opportunities to develop your skills and explore new paths. Your career at Henkel will contribute to a more sustainable future, while you grow within our vibrant, diverse culture of trust and belonging. If you're up for challenging the status quo, join our team of pioneers and make your mark on the future with us.

Do you dare to make an impact?
YOUR ROLE
  • We seek for active contribution to the Modeling Team. The team is placed in one of our global R&D platforms, and is responsible for the development and application of modeling methods for polymers, including adhesives, fiber reinforced plastics, barrier- and potting materials, etc. We develop, implement, validate, and apply digital twins to numerically predict material behavior, processes and application performance to create business value for Henkel
  • Analysis of complex applications and processes and deployment of modelling and data analyses strategies to understand and optimize material behavior, process results and application performance
  • Development, implementation, and deployment of data and theory-based modeling methods for materials connected to Henkel products
  • Combine different modeling methods, e.g. using reduced order models and IoT data, to create digital twins of materials and processes
  • Work globally with customers and all parts of the Henkel organization

YOUR SKILLS
  • University degree in Mechanical Engineering / Material Science Engineering / Physics / Civil Engineering/Numerics/Information Technology/Mathematics or equivalent field
  • Proficient in data analytics and predictive data modeling (e.g. statistics, data analysis, machine learning, optimization)
  • Basic knowledge of (cloud-based, IoT) infrastructure to support data modeling (e.g. Kubernetes, CI/CD pipelines, edge analytics)
  • Familiar with important scripting or programming tools (e.g. Python, R, Matlab) and concepts and tools used in industrial environments for data analysis and modeling
  • Experience in the behavior, characterization and modeling of polymeric materials, in particular adhesives, regarding e.g. rheology or mechanics
  • Fluent English language skills, German language skills are beneficial
Henkel is an equal opportunity employer. We evaluate qualified applicants without regard to gender, origin, culture, mindset, generation, disability, religion and sexual orientation.

Company

WE ARE PIONEERS AT HEART FOR THE GOOD OF GENERATIONS

Our purpose "Pioneers at heart for the good of generations" unites what we stand for, how we work, and forms the basis for our strategy.

The pioneering spirit of our company founder, Fritz Henkel, is what continues to differentiate us and unites Henkel employees worldwide. The ambition and motivation to work together on the solutions of tomorrow. Today. Every day. We do this not only for ourselves, but also for future generations, because we share a common responsibility.

Building on a strong legacy of more than 145 years, we are leading the way to reimagine and improve life every day. Today and for generations to come. Through our innovative and sustainable brands and technologies, across our teams around the world. Henkel holds leading positions in both industrial and consumer businesses: Our portfolio includes well-known hair care products, laundry detergents, fabric softeners as well as adhesives, sealants, and functional coatings. 

Worldwide locations and an international culture shape our global footprint.

Henkel products and technologies are available worldwide. With employees from 124 nations and locations around the world, we achieve a strong presence both in mature and emerging markets. 

 

 

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