Sort by
Refine Your Search
-
, and relevant experience; 2. a curriculum vitae; 3. contact information for one or two professional references. The application documents should be submitted via https://programs-recruiting.epfl.ch
-
Modelling (BIM), Geographic Information Systems (GIS) or computer programming is a plus. A master's degree or professional experience in architecture is preferred but not required. The employment rate varies
-
curves, zero knowledge proofs, post quantum algorithms Interest in the topics of C4DT: digital trust in general, Open Source Software, digital sovereignty Excellent command of several programming languages
-
working conditions in an international, innovative environment at a world-leading university. Flexible working hours, professional development opportunities, and work-life balance programs. A high degree of
-
. Proficiency in programming and statistics/data science. A genuine passion for music and a solid understanding of music. Fluent English and a collaborative team spirit. We offer World-Class Research: EPFL is a
-
, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related modality. Strong scientific programming in
-
scientific programming in Python and experience with GPU processing of large-scale datasets. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related
-
, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related modality. Strong scientific programming in
-
programming (Python, GIT, etc.) strongly preferred Basic cleanroom experience preferable Excellent technical problem-solving skills Open-mindedness, communication skills and critical thinking Willingness
-
, normalizing flows, VAEs, generative transformers, or related methods. Strong programming skills and experience with modern deep learning frameworks. Experience with large-scale model training, distributed