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Field
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computational biology, bioinformatics, biology, computer science, physics or related disciplines • Strong computational skills in at least one programming language (e.g. R or Python) • A strong publication record
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, epidemiology, biostatistics, data science, economics, pharmacy, medicine, or related fields Strong quantitative and programming skills, including proficiency in R, Python, or similar languages, and experience
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postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by
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programme Reference Number AE2026-0219 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0219
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programme Reference Number AE2026-0192 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0192
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: https://www.ntu.edu.sg/ase We are seeking a highly motivated Research Fellow to join a research group led by Asst Prof Zeng Yiwen. The successful candidate will work on a multidisciplinary biodiversity
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Biologist in the Gillani Lab in Computational Pediatric Cancer Research (https://gillanilab.dana-farber.org/). The Postdoctoral Computational Biologist will work on the analysis of genomic, transcriptomic
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related field. Strong background in solid mechanics, materials physics, and crystallography. Experience developing tools using Python, C/C++, MATLAB, etc. Demonstrated ability to conduct independent
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scientific programming languages (e.g. Python, R) is also valued; familiarity with international macroeconomic and trade data sources, such as UN Comtrade, UN Official Country National Accounts, or comparable
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resilience planning for the Treasure Valley. Unit URL https://iwrri.uidaho.edu/ Position Qualifications Required Experience Experience working with quantitative analysis, modeling, or data-driven methods