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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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. Machine learning will assist in artifact correction, segmentation, and material classification. By combining experimental imaging, simulation, and data-driven interpretation, this approach will deliver high
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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senior members in the lab, and at the same time to play an active role in shaping and creating inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en
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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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PI & HOSTING GROUP The direct responsible persons for this post are Dr. Joost van de Weijer and Bogdan Raducanu, members of the Learning and Machine Perception (LAMP) team at the CVC. For more
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Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
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combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce next-generation bio-based chemicals. The Computational Synthetic Biology group (CSBG), led by Dr