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Postdoctoral Researcher - Remote Sensing & Fuel Moisture Modelling Location: Christchurch or Rotorua location Duration: 2 years Organisation: Scion Research Are you passionate about using satellite
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emphasis on adhesion control, wet/underwater adhesion, soft sensors, and multifunctional interfaces. Please include a cover letter, CV with publication list, no more than three representative publications
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Postdoc position focusing on “Hydrological connectivity of soil moisture and streamflow“ in the framework of the Helmholtz Water Safety and Security Initiative: Reference Number 11039 This position is part
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project students. The research activities will take place in the state of the art facilities provided by NDCN including access to wet lab space, cell culture and advanced imaging. The Neural Injury Group
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focus on the genetic and epigenetic molecular pathogenesis of pediatric T-cell leukemia (T-ALL). One particular emphasis will be on the multiomic wet- and dry-lab analysis of clonal and subclonal genomic
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independence but with regular engagement from project PIs and collaborators. The Postdoctoral Associate will be supervised by ARAC faculty and will work closely with bioinformatics, epidemiology, and wet
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Neutron Scattering Division and Chemical Science Division, with opportunity to work with collaborators in a stimulating multidisciplinary environment across ORNL. Major Duties/Responsibilities: Perform wet
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include: Developing deep learning models for spatiotemporal fusion of multi-sensor satellite data (e.g. SAR and SMAP), with soil moisture as a target variable. Designing and evaluating deep learning
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Doctoral and Postdoctoral Researcher Positions in the Cluster of Excellence “Balance of the Microver
according to German TV-L E13 for 3.5 years) and 2 Postdoc positions (100 % TV-L E13 for 2 years) with wet-lab or computational focus to decode microbial balance in a highly collaborative and multidisciplinary
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closely with VGL's bioinformatics team, the VGL wet lab team, led by Co-Director of the VGL, Jennifer Balacco, as well as the University’s Data Science Platform (“DSP”) team, contributing to software