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Field
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Skills, Qualifications & Requirements: Required Qualifications The ideal candidate will hold a PhD in the field of psychology, neuroscience, computer or data science, physics, or physiology with brain
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. or other terminal degree in terminal degree in Civil or Environmental Engineering, hydrology, ecology, geosciences, computer science, applied mathematics, data analytics, or related fields at the start date
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well as gain or currently have proficiency in data analysis techniques including analysis of sequencing data. The candidate is expected to work independently on a daily basis, with regularly scheduled meetings
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demonstrated ability to work independently on technically demanding data tasks, with attention to reproducibility, documentation, and analytical robustness; proven experience supervising and mentoring others
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
experimentation, plant ecophysiology, functional trait ecology, and quantitative data analysis to improve our understanding of plant strategies across natural and urban ecosystems. Working with the Principal
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data science, contributing to projects that leverage cutting-edge multiomic datasets to develop predictive models of therapy response and identify clinically actionable biomarkers. Located in Boston and
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PhD in a relevant discipline and a demonstrated ability to conduct high-quality research. You bring strong analytical and communication skills, experience working with qualitative and/or quantitative
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will be an integral part of the Women’s Activities in Armed Rebellion (WAAR) research project, funded by the UN’s Complex Risk Analytics Fund (CRAF’d). The postdoc will also be invited to engage with
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description here About you You will have: PhD (or in the final stages of PhD submission) in computational biology, evolutionary genomics, computer science, or a related field* Strong analytical, quantitative
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* Develop and apply analytical pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies to identify biological signatures