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Field
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(IAMS) at Academia Sinica invites applications for the position of tenure-track or tenured Full/Associate/Assistant Research Fellow specializing in analytical technology developments for biological
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, Statistics, Image analysis Basic understanding of plant phenotyping and analysis of large data sets, preferably also using AI tools for image analysis Strong analytical skills and ability to work independently
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, economic evaluation, and surveillance to learn how to operationalize, and when needed, improve analytical tools. Research activities will support rapid risk assessment, emergency preparedness, and
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, entanglement, or resource theories is required. Strong analytical skills and publication record are essential. Experience in quasiprobability methods or operational approaches to quantumness is advantageous. We
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robotics) for field-based phenotyping Data management and analytics from multi-stream remote sensing platforms Preferred willingness to learn: Use of Python, CRBasic, Matlab, C++, R, or other programming
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, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with
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Medicine (PhARM) Program by leading rigorous pharmacoepidemiologic and policy-relevant research. The fellow will contribute to manuscript development, grant writing, analytic infrastructure development, and
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of strategies for research engagement - Experience with protocol development - Experience with data collection and management - Familiarity with data management and analytical software such as REDCap, R, STATA
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. The Fellow will work in close partnership with the lab's experimental team to build and apply analytical frameworks that translate these data into mechanistic insight and therapeutic hypotheses. As part of
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sustained, specialized effort that cannot be met by short-term or fractional support. Development of reproducible analytical pipelines and computational methods that can be shared with, adapted by, and