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Field
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Researcher Development: Supervise students, model responsible research conduct, build researcher capability, facilitate engagement for supervisees, recruit and manage employees, provide performance feedback
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Research Fellow who will work in the wider Theme B: Sustainable Food System and Supply. The post involves using sectoral datasets, and a demand elasticity matrix, to model future supply scenarios of food
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cells with greater precision, persistence, and safety, using synthetic biology, molecular immunology, and translational models. Led by Dr. William Gibson, the lab is based at Dana-Farber and Harvard
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 29 days ago
, including of heavy industry in Australia, working collaboratively with other researchers. Methods are broadly in the field of social sciences, including economics, market modelling and public policy analysis
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UiO/Anders Lien 15th August 2025 Languages English English English Postdoctoral Research Fellow in terrestrial carbon cycle modelling Apply for this job See advertisement About the position Position
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the field of social sciences, including economics, market modelling and public policy analysis. For further information please contact Dr Jorrit Gosens, E: jorrit.gosens@anu.edu.au . ANU values diversity and
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local communities and with parents. Understanding of the promotoras model of leadership. Fluent communication in both English and Spanish. Equipment Use of personal computer and proficiency in software
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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understood, modeled, and ultimately reversed or rebuilt using bioengineering and synthetic biology approaches. The successful candidate will: Investigate mechanisms of T-cell development, aging, and thymic
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work that underpins the scientific research of the collaboration. Research Title: Process Modeling using Physically Informed Machine Learning The work will entail: § Designing and training physics