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Field
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genetics, and physiology to identify fundamental mechanisms controlling muscle stem cell function and to develop innovative therapeutic strategies for muscle diseases. You will lead independent research
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Massel and Hjorth-Jensen, focusing on theoretical and algorithmic developments that enable machine-learning-assisted discovery, control, and certification of complex multimode quantum states. The work will
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to support downstream implementation Position description: P4Health CoE is seeking an ambitious and motivated Postdoctoral Researcher to join studies investigating astrocytic protein quality control in
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of “controllable” chemistries for creating and degrading linkages between bioactive semiochemicals and inactive precursory forms. This project will give you experience in bioassay-driven discovery and help develop
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environments, the use of machine learning frameworks (e.g. PyTorch) and version control tools (e.g. GitHub) is an advantage Applicants must be able to work independently and in a structured manner, and possess
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. Strong competence in programming with C/C++ or Fortran for model development & debugging. Competence in software engineering best practices such as unit testing, use of modern version control systems
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to advance basic and applied research goals, such as understanding host-pathogen interactions or efficacy of viral control strategies. You will be involved in all phases of research, with an emphasis placed
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violence, coercive control, technology-facilitated harm and justice responses. The project seeks to generate new knowledge about the pathways through which children and young people engage in harmful sexual
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-performance computing, reproducible workflow development, version control and collaborative data-science practices. Salary The expected salary range for this position is CAD $70,000 to $75,000 per annum at 1.0
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with healthcare data (e.g., EHR, clinical text, imaging, omics). Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases