94 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Switzerland
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- ETH Zurich
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are also expected. Profile PhD in Data Science, Computer Science, Mechatronics, Remote Sensing, Engineering Geology or other related discipline Demonstrated expertise in machine learning and computer vision
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Geology or other related discipline Demonstrated expertise in machine learning and computer vision algorithms is necessary, with an emphasis on object tracking, optical flow and sensor fusion Knowledge
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modeling, interpretable and explainable machine learning, or hybrid modeling by combining process-based and data-driven approaches. Besides your own main project focus, you will contribute to the supervision
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Supervision of BSc and MSc students Your profile We are looking for a highly creative self-motivated team player You have a PhD degree in Materials Science or Chemistry combined with Machine Learning In depth
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of a dynamic and international group of researchers who share a common vision to contribute to top-level academic research in the fields of machine learning. You will have access to state-of-the-art
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. The institute has also published at most of the major machine learning, computer vision, and robotics conferences, including CVPR, NeurIPS, ICCV, ECCV, ICML, ICLR, IROS, AISTATS, as well as in areas like
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The Department of Biomedicine is a joint effort between the University of Basel and the University Hospitals Basel. It unites basic and clinical scientists to advance our understanding of health and disease and to develop pioneering therapies benefiting the lives of patients in areas of unmet...
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The Department of Biomedicine is a joint effort between the University of Basel and the University Hospitals Basel. It unites basic and clinical scientists to advance our understanding of health and disease and to develop pioneering therapies benefiting the lives of patients in areas of unmet...
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capability to identify and quickly learn the most suitable tools for the research on the go. Interested in topics related to the research, such as computational design, performative design, circular economy in
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telescopes. Explore Machine Learning techniques (CNNs, DBSCAN, Transformers, etc.). Implement low-latency computing accelerators on FPGAs. Contribute to open-source ML-on-FPGA tools (e.g., HLS4ML, FINN