Lecturer / Lectureress

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Your Responsibilities

This position presents a strategic opportunity to develop interdisciplinary courses that integrate disciplinary expertise in the study of global visual cultures—both historical and contemporary—with computational analytical methods and critical approaches to digital tools and artifacts.

The successful candidate will hold a doctoral degree in one of the following fields: Art History, Visual Culture, Media Studies, Archaeology, Film Studies, Education, Digital Humanities, Digital Culture Studies, or a closely related field, with an emphasis on the computational analysis of visual materials. They will specialize in digital curation and the analysis of visual cultural data (such as artworks, photographs, maps, films and videos, digital media like memes and Instagram posts, objects, artifacts, exhibition records, and visual archives). Expertise in computational methods (including computer vision, machine learning, network analysis, data management, and digital preservation) is essential, along with a critical perspective that encompasses tool and data criticism as well as digital ethics. Proven experience in teaching computational methods within the context of visual culture studies is also required.

Furthermore, the candidate will engage in cross-institutional or transdisciplinary collaborations with experts across various disciplines and cultural areas (including Art History, East Asian Art History, Film Studies, Archaeology, Media and Communication, and Educational Sciences) to ensure disciplinary relevance and adaptability to evolving academic and technological developments.

Teaching Responsibilities

• Teach eight weekly teaching units (each 45 minutes), generally covering four courses per semester at the BA, MA, and/or PhD levels in programs such as Film Studies, Art History, Archaeology, Media and Communication, and Educational Sciences.
• Administer exams (student performance assessments).
• Participate in student information events and prepare informational materials for students.

Didactic and Institutional Responsibilities

• Engage in university-level pedagogical training.
• Offer cross-institutional training for instructors teaching the modules, covering technical fundamentals and the adaptation of the latest programs into the modules, as well as transdisciplinary didactics.

Research

• Demonstrate visible research activity in the field of Digital Humanities with a focus on visual cultural data.
• Author scholarly publications.
• Collaborate and network with research partners within and beyond the involved departments.
• Participate in conferences, contributing original research.

Your Profile

Required Qualifications:

• PhD in a relevant field (e.g., Art History, Visual Culture, Media Studies, Archaeology, Film Studies, Education, Digital Humanities) with a focus on computational analysis of visual cultural materials. Experience in the computational analysis of visual materials (documented through project portfolios, work with digital archives, or scholarly publications) and teaching computational methods within visual culture studies is essential. Understanding the diversity of various forms of cultural data beyond the Euro-American context is a valuable asset.
• Expertise in computational methods and approaches, including:
  • Digital curation and data management of visual cultural data
  • Computer vision and image analysis
  • Machine learning applications for cultural visual data
  • Mapping visual data and network analysis
  • Critical approaches, including critical data studies, tool criticism, and digital ethics
• Demonstrated experience in university-level teaching in computational methods for the study of visual cultural data at the undergraduate and/or graduate levels. Experience at the PhD level is an asset. This includes course development, delivery, and supervision of student projects. Adaptability of content for diverse audiences is expected.
• Ability to teach and supervise in English (knowledge of German is an asset, but not a requirement).

Apply online using the form below. Please note that only applications matching the job profile will be considered.

Vera Müller-Hellstern
HR Manager
personal@khist.uzh.ch