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AI-Powered Catalyst Research Engineer for CO₂ Reduction(m/f/d)

Vor Ort bei Kunden in
Senior
Flexible working hours
28 Vacation days
🇩🇪 not necessary
🇬🇧 C1

Please apply here on „MINTbund.de“ with the „Apply Now“ link/button at the top right.

Note: Please apply exclusively via our direct application link hosted by Empfehlungsbund and MINTbund.de: https://en.mintbund.de/jobs/278344/ai-powered-catalyst-research-engineer-for-co2-reduction-m-strich-f-strich-d-vor-ort-bei-kunden-in. We are looking forward to meet you!

AI-Powered Catalyst Research Engineer for CO₂ Reduction (Artificial Intelligence Direction)
Location: Berlin

 

Company Introduction:

Our customer is a research institute in Germany and dedicated to energy technology innovation, renewable energy development, and energy transition research. The institute aims to provide innovative solutions for global sustainable energy development, support policy-making, and promote collaboration between scientific research and industry. By driving energy structure optimization and contributing to carbon neutrality goals, the institute plays a crucial role in the future of clean energy.

Currently, we are seeking an R&D Engineer for Power Diversification and Conversion Technology (Artificial Intelligence Direction) to join our team in Berlin.

Job Responsibilities:

  1. Utilize AI algorithms to analyze chemical data, predict the properties of potential catalysts, and assist in designing novel catalysts with optimized activity and selectivity for CO₂ reduction.
  2. Employ robotics technology for high-throughput experiments to rapidly synthesize and test large numbers of catalyst candidates, accelerating the discovery of new materials for CO₂ reduction.
  3. Analyze experimental data from material characterization techniques, correlate material properties with catalytic performance, and guide the optimization of catalyst formulations and synthesis methods to enhance CO₂ reduction activity.
  4. Apply AI-based computational modeling techniques to predict catalyst behavior at the atomic level, simulate CO₂ adsorption, activation, and reaction pathways, identify promising catalyst candidates, and direct experimental work toward the most effective designs.
  5. Continuously learn and apply new AI algorithms and techniques to optimize predictive models and improve catalyst development strategies, accelerating the discovery and optimization of CO₂ reduction catalysts.

Qualifications:

  1. Educational Background: A full-time master's degree or above in chemistry, chemical engineering and technology, materials science, computer science, energy and power engineering, renewable energy generation engineering, electrical engineering, or power technology.
  2. Work Experience: At least three years of overseas work experience, with expertise in AI-assisted catalyst development.
  3. Professional Skills: Proficiency in AI algorithms and machine learning techniques, with strong data analysis and model-building capabilities.
  4. Communication Skills: Strong communication and teamwork abilities, capable of effectively collaborating with interdisciplinary teams.
  5. Language Proficiency: Fluent in English and/or German, with the ability to work in a multicultural environment.

Benefits:

  • Highly competitive salary.
  • Sufficient research funding.
  • Comprehensive social security and benefits system.
  • Ample career development opportunities and training programs.
  • Flexible working hours and a relaxed work atmosphere.
  • Regular international academic exchanges and technical seminars.

Interested?

If you are interested in this position, please send your resume to our headhunter's email: Kontakt-Formular . We will get in touch with you as soon as possible to provide further details about the role.

DeutschEnglish
Power Diversification, Power Conversion, AI chemical, CO₂ reduction, catalyst, CO₂ adsorption, Catalyst Research, Englisch, Chemie, Physik, MINTbund.de, Empfehlungsbund

Short profile of DMTG GmbH

Wir sind ein Personal-Service-Plattform und auf der Suche nach hochqualifizierten Fachkräfte, insbesondere aus den Bereichen Automotive/Selbstfahrendes Auto, Finanz- und IT.

Wir nutzen den Empfehlungsbund, um uns neue Zielgruppen zu erschließen und den Service bei Stellenanzeigen Schalten und unser Bewerbermangement zu verbessern

Ms. Lili Lan

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