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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-NEA-2025-0152 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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statistical analysis and coding in MATLAB/Python. The lab’s research focuses on understanding neural circuits in the descending auditory system, specifically how auditory brainstem neurons encode acoustic
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-wave). Ability to perform advanced complex network analysis (preferably with experience on NetworkX). Ability to obtain advanced graphics (e.g. seaborn). Code in Python, C and BASH. Why Texas A&M
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/business network formation in low-income countries (possibly, in conflict affected areas, CAF). We seek a candidate with expertise in both empirical and theoretical economics and strong coding skills
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skills and experience with computer codes for solving the nuclear many-body problem are considered meritorious. *The date on your doctoral degree certificate is considered the official date of completion
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they interact in a bipartite network and with abiotic environmental changes - mathematical developments - coding - tests with simulations - data analyses - paper writing - presenting results
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route de Mende, 34090 Montpellier Contact City Montpellier Website https://ibmm.umontpellier.fr/ Street 1919 route de mende Postal Code 34090 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
, easy to handle codes to make available the proposed methodologies to nonspecialists. He/she will work in contact with epidemiologists and will be provided real epidemiological data. An interest in
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disease modelling Investigating the role of non-coding RNAs in retinal development Understanding light-regulated pathways in retinal cells Applying cutting-edge techniques like single-cell RNA sequencing
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or clinical domains. Strong knowledge of MRI data formats (DICOM, NIfTI) and image preprocessing tools (e.g., MONAI, SimpleITK). Excellent programming skills, demonstrated through available code or projects