University of Bern is looking for 3 PhD positions in the areas of machine learning and computer vision. One position is on motion estimation tasks (such as optical flow and structure from motion) via deep learning. The other two positions are on unsupervised learning methods for image processing also based on deep learning. Research objectives include the development and analysis of generative models for images and videos, and the development of novel machine learning methods. Research will be performed in the Computer Vision Group at the University of Bern.
The three PhD candidates will collaborate in an interdisciplinary GOA project called “Understanding Ideological Bias through Data-Driven Methods”. Ideological bias concerning age, gender, ethnicity and social class is one of the most important ethical concerns in contemporary society. From racism in social media, over sexism in advertising, to ageism and class prejudice in societal governance: all human interaction is structured by bias on explicit and implicit levels.
One PhD candidate will create a library of food components with suitable functional properties for robotic food applications, and studying methods to obtain those components from raw materials. For example, food materials that show responses to electrical, chemical, or thermal stimulations will be investigated. The second PhD candidate will focus on assembling food components into functional parts of the edible robots, and on assessing the nutritional profile and life cycle of the robots.
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