Achim Kamelger

Achim Kamelger, PhD has a diverse work experience in various roles and industries. Achim started their career at Dalhousie University as a Visiting Research Scientist in 1997. Achim then moved on to Leopold-Franzens Universität Innsbruck where they worked as a Research Scientist specializing in Remote Sensing from 2000 to 2003. In 2003, they joined OMV Exploration & Production where they held roles in Application Support and Innovation Projects until 2006. From 2006 onwards, they worked at OMV Group (Aktiengesellschaft), holding positions such as Global Manager of OMV E&P Information & Data Management and Enterprise Architect at OMV CIO Office, IT Strategy & Architecture Group. Achim'smost recent role at OMV Group was Chief Enterprise Architect.

Achim Kamelger, PhD, has a strong educational background in geology and numerical modeling. Achim began their academic journey in 1988 at Leopold-Franzens Universität Innsbruck, where they obtained a Mag. rer. nat. degree in geology after completing their studies in 1995. Throughout this period, they developed a solid foundation in geological concepts.

Seeking further expertise in their field, Kamelger pursued a PhD in geology and numerical modeling at the University of Basel from 1995 to 2001. During this six-year period, they focused on advancing their understanding of geology and applied numerical modeling techniques to enhance their research skills.

In 1997, Kamelger briefly attended Dalhousie University, where they also pursued a PhD in geology and numerical modeling. Although the duration of their studies at Dalhousie University is not specified, it suggests that they may have engaged in a short-term program or participated in specific research activities.

Additionally, Kamelger has obtained the certification TOGAF 9.x, although the details regarding the institution, month, and year of achievement are not provided.

Overall, Kamelger's educational background demonstrates their dedication to geology and their commendable efforts in exploring numerical modeling techniques for geological research.