Postdoctoral position - Laboratory for experimental museology

WorkplaceLausanne, Lake Geneva region, Switzerland


The Ecole polytechnique fédérale de Lausanne (EPFL) is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of 16,000 people, including over 10,000 students and 3,500 researchers from 120 different countries.

The Laboratory for Experimental Museology (eM+) is a leading transdisciplinary initiative at the intersection of immersive visualization technologies, visual analytics, aesthetics and cultural (big) data. eM+ engages in research from scientific, artistic and humanistic perspectives and promotes post-cinematic multisensory engagement using experimental platforms (known as location-based entertainment). eM+ has 11 unique large-scale visualization systems combined with powerful sonic architectures that are benchmarks in the realms of virtual, augmented, mixed realities. These cluster-based 3D systems are deployed in major exhibitions and interactive installations at prestigious organizations throughout the world.

We are recruiting a new postdoc to join the Laboratory for experimental museology for the upcoming SNF Sinergia interdisciplinary project involving experts in machine learning, visual analytics, digital museology, and archival science to create a groundbreaking visualization framework for interactively (re)discovering hundreds of thousands of hours of audiovisual materials. Narratives from the long tail: transforming access to audiovisual archives draws on hundreds of thousands of hours of audiovisual material from leading digital archives: Radio Télévision Suisse, the UNESCO Memory of the World listed Montreux Jazz Festival archive, and the Netherland’s Eye Filmmuseum’s Mutoscope collection.

Main duties and responsibilities include :

These vast archives demand new solutions from those who want to engage with them. to: deliver computational transformations in the data curation to augment conventional archives with richer semantic meaning; design a narrative visualization framework, combining spatio-temporal, social, aesthetic and affective semantics to pioneer new audiovisual storytelling formats and; to develop platforms for the navigation, exploration and creative reorganization of moving images through immersive and interactive systems, for broad publics in museums. Your opportunity to join and international team of experts in bringing this seminal project to fruition.

Key responsibilities

Your profile :
You have passion for research into the future of museum experience and archives through immersive and interactive visualization. You have:

strong experience in software development and are proficient in C, C++ and Python, with general knowledge of scientific programming libraries (gsl, MPI) and computer graphics (OpenGL, VTK), as well as proficiency in standard games engines (specifically Unreal Engine)

experience in production tools for code management, testing and validation, and CPU and GPU code profiling documentation (GitHub, GitLab etc)

a reasonable understanding of audio infrastructure for immersive and interactive virtual reality systems at eM+

very good analytic skills; project design and project management including implementation with several stakeholders not located on site

a passion in interactive visualization, design and virtual reality systems of the future

an interest in applied world of museums, in the futures for mass digital archives in immersive systems design for mass publics worldwide

A unique framework at the forefront of innovation of visualization and immersive experience

Start date :
June 1st 2021

Term of employment :
Fixed-term (CDD)

Duration :
1 year renewable (CDD), 4 years maximum

Remark :
Only candidates who applied through EPFL website or our partner Jobup’s website will be considered.


In your application, please refer to and reference JobID 49770.

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