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Field
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imaging (crucial) Experience with image segmentation, deep learning, or computer vision. Experience with 3D image processing or inverse problems. Experience with experimental research and data acquisition
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Strong Python skills and experience with data manipulation Basic machine learning knowledge (equivalent to at least an introductory course) Additional skills (nice-to-haves) Experience with website
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attention to quality, integrity, creativity and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural
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designs, techniques and their implementations which are of material significance in addressing important problems). Excellent computer skills and excellent communication skills to effectively interact with
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and qualifications Your principal focus will be on applied research advancing bioinformatic analysis, machine learning and computational genomics of microbial pathogens, primarily on bacterial AMR and
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. Support workforce development and training programs associated with the center. Teach occasional undergraduate or graduate courses within the Rail Transportation Engineering (RTE) program when needed
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data • Design clinically meaningful benchmarks and robust evaluations • Publish at leading machine learning and medical AI venues • Collaborate with clinicians, computer scientists, and European partners
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mathematics, machine learning, photonics, and clinical practices in vision. Be part of a multidisciplinary research team spanning science and engineering, psychology, and healthcare. Access state-of-the-art
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evaluation, validation against ground truth, and transparent reporting. Demonstrated research experience in computer vision and deep learning applied to biological microscopy data - including image
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candidate for a full-time (100%) PhD position for 3 years. You will join the research group Power Electronics and Electrical Machines (PEM) at IEL, where we foster an open, inclusive, and collaborative