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Field
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analysis and a basic knowledge of causal inference would be an advantage. Training and support in new areas will be provided. The appointed individual will be based at the Leicester Diabetes Centre
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employing Regression Discontinuity Designs (RDD) and related causal inference models, with a strong emphasis on advancing statistical methodology. The project presents significant methodological challenges
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integrating large complex datasets is likewise essential as is training in Bayesian sample assessment methods. The post is based in UCC and requires the successful candidate to work closely and in person with
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metabolism in the human fungal pathogen Cryptococcus neoformans Jonathan Doucette Doctor of Philosophy in Physics (PhD) Probing Brain Tissue Microstructure with Magnetic Resonance Imaging through Bayesian
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chart review, administering follow-up surveys to participants, completing payments, updating tracking systems, and performing various quality assurance, data entry, and data cleaning tasks. This is a
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and implementing appropriate empirical strategies for causal inference, particularly in econometric analyses. Assist in designing new econometric models or adapting existing ones to address evolving
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following up with participants who need reminders to complete study activities via phone call, email and text message Completing detailed participant tracking forms accurately and efficiently using Ripple, a
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; FACS; training will be provided) Input data, analyze data, track participants for follow-up sessions, attend lab meetings, maintain lab rooms/supplies/equipment, and prepare manuscripts. Helping with
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, Operations Research, Management Science or other relevant fields for no more than five years prior to the commencement of the appointment. Applicants should have a strong track record in research evidenced by
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visits or online assessments, tracking of overall research project progress, as well as running participants through in-lab study protocols. They will also be responsible for supporting IRB protocol