The
Chair of Landscape Architecture, led by Prof. Teresa Galí-Izard at the Institute of Landscape and Urban Studies (LUS), is part of the Department of Architecture at ETH Zurich. The
Chair of Being Alive investigates the relationship between landscape architecture, ecology, and territorial transformation through design-led research and teaching.
The
Digital Design Methods I (DDM-I) module is a foundational component of the Master of Science in Landscape Architecture programme. It introduces incoming international students-from backgrounds in architecture and landscape architecture-to the computational tools and workflows essential for landscape design at ETH Zurich. The module follows a DDM curriculum designed by Zhao Ma.
Job description This is a fixed-term position running from September through December each year. The role is structured in two phases: an intensive teaching phase (September-October) with regular weekly sessions, followed by a lighter support phase (November-December) with involvement on an as-needed basis for student follow-up, grading, and coordination.
As DDM-I Instructor, you will be responsible for:
- Delivering lectures and hands-on exercises in Digital Design Methods I (DDM-I) for the first-semester MSc Landscape Architecture cohort
- Teaching Rhinoceros 3D and Grasshopper with a focus on data structures, data manipulation, and parametric workflows for landscape design applications
- Teaching QGIS for geospatial analysis in the context of landscape and territorial design
- Guiding students through the Being Alive: Language and Being Alive: Terrain exercise sequences as defined in the DDM-I curriculum
- Assessing student exercises throughout the teaching period
- Coordinating with the Chair of Landscape Architecture on course delivery and pedagogical approach
Intensive Phase (September - October) Classes take place from mid-September through mid-October. Sessions run on Monday afternoons (13:45-15:30) and Wednesday afternoons (15:45-17:30), with the exception of the first week, which runs Tuesday and Thursday at the same times. Detailed session dates will be provided upon appointment.
Support Phase (November - December) During November and December, involvement is required on a sporadic, as-needed basis. This may include final assessment review, individual student consultations, grading support, and coordination with the chair on course evaluation and documentation.
Profile Required Qualifications
- Advanced proficiency in Rhinoceros 3D and Grasshopper, including deep understanding of Grasshopper data structures (trees, branches, paths) and data manipulation techniques. This is essential and non-negotiable.
- Background in landscape architecture with demonstrated experience in landscape design. Candidates must understand the discipline's specific design thinking, ecological considerations, and spatial methodologies.
- Proficiency in QGIS or equivalent GIS tools for geospatial analysis
- Experience in teaching, tutoring, or workshop facilitation in a higher education or professional setting
- Excellent communication skills in English (the programme's language of instruction)
Additional Qualifications (Assets)
The following skills are not required but will strengthen your application:
- Active GitHub profile with a tracked commit history demonstrating software development practice and open-source contributions
- Development experience with C#, particularly in the context of Grasshopper plug-in development or Rhino scripting (RhinoCommon)
- Demonstrated experience with agentic development - e.g., building AI-assisted workflows, LLM-based toolchains, or autonomous design agents
We offer - A stimulating academic environment at one of the world's leading universities of science and technology
- The opportunity to contribute to an innovative, design-led landscape architecture programme
- Collaboration with an internationally recognised research chair at the forefront of landscape and ecological design
- Competitive compensation in accordance with ETH Zurich employment guidelines
- Access to ETH Zurich's state-of-the-art computational infrastructure and facilities
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