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Postdoc in Generative Machine Learning for Biomedical Data | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 21.02.2026 Join a place where
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curious to deliver work that matters, your journey starts here! The Biomedical Engineering Department at Carnegie Mellon University is renowned for its interdisciplinary approach to solving complex
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/abstracts and presentations 5% -Attend lab meetings and weekly 1-1 meetings with advisor(s) 5% -Contribute to essential lab chores and maintain lab safety Qualifications Required Qualifications: PhD degree in
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scientific publications Specific Requirements PhD degree in chemical sciences, materials engineering, biomedical engineering, or a related discipline, obtained within 7 years prior to 1 January of the year of
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are expected to have a PhD in Physics, Mathematics, Computer Science or a related quantitative discipline. Ideal candidates from the biological sciences should have experience with scientific programming. Ideal
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skills. Effective mentorship and team collaboration abilities. Knowledge of regulatory compliance (IACUC, IRB, biosafety). Minimum Qualifications PhD, MD, or equivalent doctoral degree in biomedical
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as a one‐year appointment, but renewable annually based on performance. The position involves postdoctoral work in developing efficient methods and tools for analyzing large-scale biomedical data with
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, or soon-to-be-awarded, PhD in cancer biology or a related biomedical field. Previous experience working with organoid culture systems. Experience in molecular biology techniques (flow cytometry, viral
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biology, bioinformatics, computer science, biology, or a related discipline, Strong interest in applying quantitative approaches to complex biological and biomedical questions Solid computational skills
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molecular mechanisms by which endocytic structures remove damaged proteins in human physiology and neurodegenerative disorders. Successful candidates will have: A PhD in cell biology, neuroscience, or related