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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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. PyTorch). Experience analyzing high-dimensional data (biological or otherwise) or single-cell, bulk sequencing, or other biological data. Experience in algorithms and good software development practices
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computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET
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in healthy states, genetically perturbed states, and during liver regeneration. On the other hand, you will develop algorithms to disentangle direct intercellular signals from those that are induced
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demonstrated experimental realizations and proven theoretical advantages. The project may involve several aspects, including mathematical theory, algorithm development, error correction, adaptation of GBS-based
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of expertise offers unique opportunities to address the complex challenges of modern society, to develop comprehensive new approaches, and educate the problem-solvers of tomorrow from a multidisciplinary
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
of this project requires the design, development, and training of an artificial intelligence algorithm capable of automatically segmenting the bony structures of both healthy and fractured tibial plateaus
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to implement the Data Strategy, develops and implements standard programming practices while also ensuring that they are employed across a study or program. What You’ll Do Leads, coordinates and manages timely
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opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training