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models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
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*Strong publication record (relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM
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. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected to have hands-on experience in field related to urban or rural planning, renewable
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university deep tech startups, carry out independent, high-quality research leveraging this data, and engage with stakeholders in the Danish and international deep tech arena. Responsibilities and
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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medication use Applying frameworks such as the Andersen Behavioral Model (ABM) and 4Ms of Geriatrics Conducting advanced data analysis and predictive modeling Engaging patients, caregivers, and health system
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, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6. Further Information We
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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to the development of ongoing research. This will include the integration, modelling, and advanced statistical analyses of large genetic, ecological, and environmental data sets. The successful candidate is also
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and/or issues using discretion; experience with tritium transport modelling, hydrogen in materials, or fusion blanket concepts; familiarity with data assimilation, uncertainty quantification, or large