[ref. f08019620] Technische Universität München - Research Associate in interdisciplinary research project NERF2BIM - AI-Driven Detailing-on-Demand through Sustainable Point Cloud Surveys and Semantic 3D Understanding for Advanced Modeling of Existin
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Technische Universität München
Research Associate in interdisciplinary research project "NERF2BIM - AI-Driven Detailing-on-Demand through Sustainable Point Cloud Surveys and Semantic 3D Understanding for Advanced Modeling of Existing Buildings" funded by the Georg-Nemetschek-Institute with the option for a Doctoral Degree
- 09.2024, Wissenschaftliches Personal
The interdisciplinary team at the Chair of Architectural Informatics deals with digitalization topics in the fields of architecture in teaching and research and serves as a bridge between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods.
As part of the interdisciplinary research project "NERF2BIM - AI-Driven Detailing-on-Demand through Sustainable Point Cloud Surveys and Semantic 3D Understanding for Advanced Modeling of Existing Buildings" funded by the Georg-Nemetschek-Institute, methods of artificial intelligence for the built environment will be developed in collaboration with teams led by Prof.Dr.-Ing. Matthias Niessner (Chair of Visual Computing and Artificial Intelligence, School of Computation, Information and Technology) and Prof. Dr.-Ing. Christoph Holst (Chair of Engineering Geodesy, School of Engineering and Design)
Your Responsibilities:
Collaboration in the research project "NERF2BIM" / sub-project "AI-based knowledge-driven reconstruction of semantic building data using multiple image data sources"
Research and development into knowledge-driven systems with the integration of human feedback
Providing scientific Publications and Presentations in English.
Contribute to the academic university environment by supervising students.
The above-mentioned subject areas define the content of the job profile. The applicant's own thematic priorities are welcome and can be included in the formulation of the research project.
Your Qualifications:
A university degree (master's or diploma) in either computer science, architecture, civil engineering, or geodesy with a specialization in Deep Learning, or in a comparable thematically appropriate discipline.
In-depth skills in programming and working with Deep Learning methods.
Expertise in the field of Building Information Modelling, ontologies, and point clouds is greatly beneficial.
Experience in publishing scientific texts.
Confident in written and spoken English (C1 or greater).
Written and spoken German is beneficial.
Enthusiasm for the challenges of digitalization in the built environment and artificial intelligence.
Capable of and interested in analytical, creative, and interdisciplinary thinking.
High level of commitment, independence, and initiative.
Systematic way of working and high reliability.
Ability to work in a team and to communicate
Our Offer: We offer you a diverse and fulfilling job in a modern, renowned university, a pleasant working atmosphere, and collaboration on interesting research projects. You will work independently in a dynamic, team-oriented, and interdisciplinary environment with various objectives.You can expect a modern, well-equipped workplace in a central and convenient location in Munich.
If you are interested, please send your complete and compelling application documents no later than 31.10.2024 by email to the address below. Please use the keyword [NERF2BIM] in the email's subject header.
info [at] ai.ar.tum.de
www.arc.ed.tum.de/ai/
Prof. Dr.-Ing. Frank Petzold Lehrstuhl für Architekturinformatik Arcisstrasse 21 80333 München
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Kontakt: info [at] ai.ar.tum.de
- Computer Science - Informatique - Informatik
- Architecture - Architecture - Architektur
- Reference: jobs.myscience.de/id200917