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Field
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Postdoc Position for Computational Genomics, AI Precision Oncology, Cancer Biology and Immunobiology
University of Pittsburgh, Pittsburgh , Pennsylvania, US | Pittsburgh, Pennsylvania | United States | about 2 months ago, IMPREG signature) for precision immuno-oncology panels. Preferred qualifications: Ph.D. in bioinformatics, computational biology, computer science, statistics, or a related field. Strong programming skills
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systems using large-scale single-cell and spatial multi-omics data. This position goes beyond conventional bioinformatics analysis and focuses on methodological innovation at the interface of AI, systems
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trusted voice in digital health, technology and transformation. The Research Assistant Professor will serve as the MIL site expert in bioinformatics setting the strategic vision for the group, leading
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Description of programme/project/undertaking Recent developments in biotechnology, including the enormous progress in sequencing technologies and public accessibility to many bioinformatic data, create new
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efficiency. You will be embedded within a multidisciplinary team of experts in artificial intelligence, bioinformatics, laboratory automation and synthetic biology. While the wider team develops AI-driven
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Technologies (Empa) with often visits to collaborators in Zurich. The fellow will also be affiliated with the Swiss Institute of Bioinformatics. We offer outstanding conditions for excelling in the field
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first-author publication: computational biology/bioinformatics, metabolism/metabolomics, analytical chemistry/mass spectrometry, cheminformatics, or machine learning/computer science. Prior experience in
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of Pittsburgh. DBMI has eighteen primary faculty members with a focus on developing and applying AI/ML methods in clinical informatics, translational bioinformatics, clinical research informatics, and public
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(bioinformatics, genomics, …) and research experience in the field of cancer genomics, although we welcome applications from candidates with diverse educational backgrounds, including computational biology, physics
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of many teaching and research awards, with strengths in the Department including algorithms, artificial intelligence and machine learning, data science, bioinformatics, computational neuroscience