Computational Chemist
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My strong analytical and systematic approach enables me to solve complex problems efficiently and develop innovative solutions. I can quickly immerse myself in new subject areas and employ modern technologies to achieve optimal results. My experience in data analysis and computational models aligns well with the requirements for this position.
Additionally, I have successfully coordinated cross-functional projects and collaborated with various partners, underscoring my teamwork and communication skills.
I have recently completed my Ph.D. in Technical and Theoretical Chemistry with a focus on heterogeneous catalysis at the Karlsruhe Institute of Technology. My dissertation involved investigating Pd and Pt noble metals in various sizes supported on ceria, utilizing quantum chemical theories to examine chemical processes and applying microkinetic models. This work provided me with a deep understanding of complex systems and the ability to model intricate processes effectively.
My theoretical knowledge in artificial intelligence, molecular dynamics, machine learning, and neural networks was honed through various projects in my research environment. My profound theoretical education in theoretical chemistry, as well as in simulation and modeling, allows me to quickly learn and apply new methods. I am very eager to now undertake my own projects using ML methodology.
Studt und Dr.
Plessow über die theoretische Untersuchung der Ethanolumwandlung über saure Zeolithe.
