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of Violence against Women (CEVAW) plays a vital role in analysing and visualizing statistical data to support research on violence against women. They provide advanced analytical services, consult with
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Computational econometrics or statistics Econometric or statistical computing Data science Machine learning Operations research Candidates should be prepared to teach in both business analytics and econometrics
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the ability to establish and achieve goals Excellent written and oral communication skills, with a collegial approach to teamwork Advanced computer skills, including Microsoft Office and analytical software
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tasks such as comprehensive literature reviews, data analysis and scientific publications. We seek candidates with a doctoral qualification in a relevant discipline or equivalent qualifications
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, overseeing research procedures, and analysing data. Engaging in preclinical work utilizing rodent trauma models, neuropharmacology, neuroimaging (e.g., MRI), and cellular and molecular methods. Participating
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longitudinal studies and data analysis. Produce conference and seminar papers, as well as research publications. Contribute to research proposal submissions for external funding. Engage in professional
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candidate, you will bring extensive expertise in reviews, governance management and policy development. Your strong organisational, interpersonal, and analytical skills, along with advanced computer literacy
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Proven track record in analytical research and publication A demonstrated capacity to collate, curate and analyse large bacterial genome datasets Proficiency in Python/R for data analysis and visualisation
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participant recruitment to data analysis, all aimed at supporting the lab's research program. You will work with state-of-the-art equipment like functional magnetic resonance imaging and transcranial magnetic
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undergraduates Managing a budget of up to $75,000 and co-supervising 5 PhD students Key Selection Criteria: Doctoral qualification in a relevant field Strong analytical and manuscript preparation skills