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. This program offers a rare opportunity to combine methodological independence in artificial intelligence and biology with direct access to real-world clinical and translational research data, addressing global
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instrumentation (single-cell mass spectrometry, high-resolution microscopy, next-generation sequencing) and artificial intelligence-guided computational workflows. Job Description Develop computational image
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Intelligence (AI) approaches and methods with the long-term objective of improving clinical cancer care. The training, project development, and application will be mentored by Dr. Peter Nelson and Dr. Jeff Leek
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ICT Services & Applications. Your role The successful candidates will join the Computer Vision, Machine Intelligence and Imaging research group, led by Prof. Djamila Aouada, to conduct research in
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
more than 20 countries. We perform basic and applied research within plants, livestock and human quantitative genetics. Our focus areas include quantitative genetics, breeding plans, artificial intelligence
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human health. Within this mission, the Iorio Group works at the intersection of computational biology, functional genomics, and precision oncology, integrating machine learning, large-scale CRISPR
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& Intelligent Precision Therapy, Clinical Research & Big Data in Ultrasound Therapy. Required Disciplines: Physics, Electronics, Instrumentation, Materials, EE, Biomedical Engineering, Computer Science, Mechanics
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human health. Within this mission, the Jug Group develops advanced computational methods and open scientific software to extract knowledge from complex biological imaging data. We work at the intersection
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engage with collaborators across Belgian universities. Profile Education: PhD in Artificial Intelligence, Bioinformatics, Computer Science, Physics, Engineering, or a related field. Programming
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until an excellent fit is found. The successful candidate will develop and apply computational approaches to biochemical datasets, with artificial intelligence/machine learning (AI/ML) being a major focus