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Postdoctoral Fellow in Anthropology: Meat, Infrastructure, and Zoonotic Risk on Chinas Belt and Road
, UiT -The Arctic University of Norway email: rita.johansen@uit.no via Unsplash Qualifications Required qualifications PhD in Social, Cultural, Visual Anthropology or closely related discipline. If you’re
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performance management system. Physical Requirements (With or Without Accommodations): • Visual acuity to read information from computer screens, forms and other printed materials and information. • Able
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electrochemical techniques. Experience with data visualization and analysis software. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background
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an inclusive, collaborative research culture. Methodological Innovation (10%): Contribute to the development of advanced analytic plans, causal methods, and data visualizations that highlight intervention
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Learn, OpenCV, PyTorch), R, SQL, HTML/CSS, C, STATA Coursework in Machine Learning, Algorithms/Advanced Data Structures, Data Science, Probability, Data Graphics and Visualizations, Modern Regression
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-dimensional visual stimuli (https://doi.org/10.1101/2024.09.27.615442), and how the inputs onto single depth-selective neurons give rise to their response properties. To accomplish this, this project, which you
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modelling, simulation, and visualization functionalities, as planned in the European project ARTEMIS - Applying Reactive Twins to Enhance Monument Information Systems. Activities may include designing and
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visual cues, attractants, pheromones, and trap crops. The participant will study the impact of agronomic and cultural practices on the development, population dynamics, and distribution of cotton jassids
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to characterize immune and tumor cell phenotypes. -Execute standard molecular biology techniques, including PCR, Western blotting, and gene expression analyses. -Apply confocal microscopy to visualize cell-cell and
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bioinformatics pipeline aligns with overall research objective. Visualize and communicate complex microbiome data in a clear and accessible manner for interdisciplinary teams. Contribute to formulating hypothesis