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" button. We would like to point out that data will be transmitted to OpenStreetMap after activation. You can find out more in our privacy policy. You can revoke your consent to the transmission of data
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the
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technologies to process your personal data (e.g. IP address) for personalised content, ads and third-party media integrations. Functional and strictly analytical cookies are always set. Non-essential and non
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total of approximately 1,400 employees and 17,700 students spread across two inspiring campus environments in Karlstad and Arvika. More information at: kau.se/en/work-with-us Description The Faculty
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Midlands Graduate School Doctoral Training Partnership | Birmingham, England | United Kingdom | about 2 months ago
of evidence-based interventions. The chosen candidate will join a strongly multidisciplinary team and learn clinical skills alongside academic skills related to review of the literature, research design, data
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data availability and design parameters. Importantly, the AI implementation should act as a facilitator of creativity, enhancing, and inspiring the early design phase rather than constraining
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clinical and drug development precincts at Monash and has a number of major industry partnerships to facilitate the translation of our research. For more information about the BDI please visit our website
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based
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behaviour and system efficiency. Uncertainty is inherent in the design of subsurface energy technologies, particularly during early-stage development when data may be sparse, incomplete, or inaccessible