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University College London, this role offers the opportunity to contribute to cutting-edge research on dietary change, environmental, health, and economic impacts of food systems. Working with Dr Marco
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relationships describing the emission, fate and effects of pollutants as a function of size. We intend to derive overarching scaling principles that apply across multiple disciplines, including hydrology
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/Qualifications The successful candidate (m/f/x) is expected to actively contribute to the above project. The Post-Doctoral project should study the work and impact of (networks of) local and Indigenous plant
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; (2) Conduct ocean OSEs for hurricane forecasts, using weakly coupled data assimilation integrated into the coupled Hurricane Analysis and Forecast System (HAFS). The appointee will work closely with
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Job Description Apply now Job Title: Postdoctoral Associate Division: Human Genome Sequencing Center Work Arrangement: Onsite only Location: Houston, TX Salary Range: $62,232 - $70,000 FLSA Status
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: Previous experience with data analysis would be a plus but not required. Language skills : Perfect fluency in English is required. Abilities Applicants should be able to work interactively in a collaborative
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functional analysis as well as the theory and numerics of PDEs. Strong skills in math. modeling with PDEs Advanced knowledge in numerics and simulation, particularly for PDEs and especially with FEM Strong
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Postdoc in experimental studies of phase behavior of ABC-miktoarm star block copolymers in thin f...
Experience with image analysis Experience with coding and high-performance computing, for example in python, C, etc. Experience with polymer and/or block copolymer physics and/or chemistry Experience with
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; develop projects, collects data, and conducts quantitative and qualitative analysis in new research projects designed as pilot work for new grant submissions; participates in bi-monthly research team
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motivated to advance trustworthy artificial intelligence in medical imaging? In this postdoctoral position, you will work on explainable AI and foundation models for CT imaging, combining methodological