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compliance of the developed methods. There will also be interaction with the Novo Nordisk Foundation Data Science Infrastructure Programme,“the National Health Data Science Sandbox”, a network of data
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of data as well as related tools and systems. At the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain) we develop the next generation biotechnology using synthetic biology techniques. We
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Compounds to Elucidate the Structure of Polycystic Ovarian Syndrome (SUCCESS)”, financed by Novo Nordisk Foundation. About the project/work tasks: The project is related to digital medicine and artificial
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collaboration with a research group at Stanford University and ”System dynamics approach Using Chemical Compounds to Elucidate the Structure of Polycystic Ovarian Syndrome (SUCCESS)”, financed by Novo Nordisk
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Ovarian Syndrome (SUCCESS)”, financed by Novo Nordisk Foundation. About the project/work tasks: The project is related to digital medicine and artificial intelligence, particularly the goal of developing a
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Hybrid Quantum Chemistry on Hybrid Quantum Computers , funded by the Novo Nordisk Foundation, we have an opening for a two-year postdoctoral to work on the development of quantum chemical methods and
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questions about glycolysis based on the results. These projects are funded by a Novo Nordisk Foundation Laureate grant. Responsibilities and qualifications You will work as part of a team to improve the
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Postdoc in statistics to develop Bayesian privacy metrics for synthetic health data (2024-224-05725)
scientist, students, and a student helper. The project is a part of the ambitious Novo Nordisk Foundation Data Science Collaborative Programme,“Synthetic health data: ethical development and deployment via
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-world challenges. At The Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain), located on the Technical University of Denmark’s main campus near Copenhagen (Kongens Lyngby), we develop
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Novo Nordisk Emerging Investigator fellowship, a grant from the Independent Research Fund of Denmark and other sources of funding. We focus on the development of statistical and machine learning