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Field
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analysis experience and scientific writing ability Experience with systematic or scoping reviews (or other structured knowledge-synthesis methods) Experience in R or Stata Knowledge of experimental and
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methods and statistics. Specialist skills in bronchoscopy, EBUS and teaching are desirable with a willingness to learn new skills. The post holder will be required to work independently and as part of a
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under supervision of a project leader Collect research data; this may be through a variety of research methods, such as scientific experimentation, computer or numerical simulation, literature reviews
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Contribute to experimental measurements in the nuclear medicine clinic for research purposes Contribute to developing improved SPECT/CT and PET/CT image segmentation and reconstruction methods including AI
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-, Master's- and PhD degrees. If you have not yet completed your PhD, you must provide confirmation on your estimated date for the doctoral dissertation, or confirmation that your PhD thesis has been submitted
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projects. Required Licensure/Certification/Specialized Training: • None Preferred Licensure, Certification, and/or Specialized Training: • None Knowledge, Skills & Abilities: • Knowledge of research methods
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codesign fieldwork methods with long-term partners in the Hunter Valley to understand community perceptions of, and backlash to renewable energy infrastructure. We will also develop expanded, critical
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Computer Engineering. More information on the laboratory is available at www.neuroimaginglab.org . The MNNDL group at NUS is a multidisciplinary team studying the human neural bases of cognitive functions
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. Background preparing and presenting work at meetings. Technical Skills or Knowledge: Extensive knowledge in a relevant field of economics. Sound research techniques and/or methods. Preferred Competencies Work
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. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast