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(pre-screened) by multiple people independently. Personal interviews follow in the next step. Language requirements Proficient English skills Submit application to E-mail: application@mcml.ai
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cornerstone of medical treatment. A large portion of all hospital patients suffer from multiple diseases and are already undergoing a complex drug therapy at the time of admission. For the most successful
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on the quality of the accepted abstract and alignment with the goals of the New Zealand Coastal Society. To be eligible the abstract must be accepted for presentation at the Australasian Coasts and Ports
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the State more attractive to funders of clinical trials (grant funding and commercial sponsors). The expected outcomes are in alignment with the following objectives of the Western Australian Future Health
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Stream applications are initially assessed for general PSI eligibility, followed by an evaluation based on factors including the overall application quality, alignment with the Health Equity Stream goals
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 2 hours ago
proposal, it is essential to ensure that the research proposal topic aligns with the research areas of the PhD programme. Language requirements A certificate of proficiency in English must be provided
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 2 hours ago
). The application includes a comprehensive research proposal . While you have the autonomy to choose the research topic for your proposal, it is essential to ensure that the research proposal topic aligns with
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Assistant Professor (non-tenure eligible). Research Assistant Professors are eligible for multi-year appointments that align with a 12-month service period (July 1-June 30). Faculty with 12-month service
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supported by an ARC Industry Fellowship, in partnership with Bush Heritage Australia. This project will align with Bush Heritage’s Right-Way Science policy. Bush Heritage will provide a generous top-up and
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case