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recognized basic and/or translational research program, provide service to the Institute, Department, and University, and mentor trainees in vision science. A competitive start-up package, excellent laboratory
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) Applications
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and knowledge transfer. Discipline, including, but not limited to: Electronic and Information Engineering, Computer and Data Engineering, Electronic and Electrical Engineering, Information Engineering
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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period CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD
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, functional genomics (e.g. saturation mutagenesis), and molecular engineering are highly welcome. Designed for accomplished graduates with a clear scientific vision, GIS Fellow Programme enables successful
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. This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design, and
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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints