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. This includes exploring the use of digital twins for bioreactors and deploying AI driven predictive models to improve optimisation, consistency and overall yield. The main focus for this role is to work with the
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models, and the discovery of novel pathways involved in both normal development and disease, driving progress in regenerative medicine and personalized healthcare. Where to apply E-mail positions@gimm.pt
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have extensive knowledge on processes governing cross-shore transport and can use experimental data to develop predictive models. Experiences within numerical modelling of coastal processes is considered
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interdisciplinary initiative focused on advancing Predictive, Preventive, Personalized, and Participatory (P4) approaches in health and medicine. Within the IRAP framework, the project’s scientific goal is to
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the Norwegian Institute for Nature Research (NINA) and partners in 14 countries. For more information, see: https://seatrack.net . This is a fixed termed position for 3 years in our section for terrestrial
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segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware predictions across scales. This role requires deep knowledge of the underlying models and
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these models for scalable vision tasks, instance segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware predictions across scales. This role requires
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outputs and insights, you will further extent the research to prediction models and different product development, which can be tested on pilot scale as well. Duties As a Ph.D. student you are expected
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Silva. Grant duration: Initial duration of 36 months, with the predicted starting date in April 2026, on an exclusive basis eventually renewable but never exceeding the project duration
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main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three different research themes: (1) Planets