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conferences. • Contribute to the writing of scientific publications. Optional : • Design Machine Learning (ML) potentials. • Code in FORTRAN and PYTHON to improve the functionality of the global
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
from extreme weather to pandemics to cyberattacks. - Applicants must have significant computer coding skills, e.g., Python, R - Excellent written, oral, and interpersonal communication skills. Preferred
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interests Three letters of reference More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Completed applications will be reviewed as received, with all applications submitted
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econometric methods for analysing large datasets. Are proficient in coding and data management using tools such as Stata, R, or Python. Have a strong interest in the research area and have a strong independent
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of Medical Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research
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, culinary, and international experience. More info on Iowa City can be found at https://wessel.lab.uiowa.edu/iowa-city . Highly-motiviated scholars with the attributes listed in the requirements section below
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setups, including the development of software required to gather and analyse data (using e.g., .Net, Python, LabView); Experience in the operation of common clean room tools used in the nanofabrication
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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, comparative genomics) OR experience in computational proteomics Strong programming skills in Python and R, proficient in complex bioinformatics workflows Strong communication skills, ability to work in
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highly motivated Postdoctoral Scholar to work at the interface of fire ecology, forest dynamics, and ecosystem modeling as part of the Western Fire and Forest Resilience Collaborative (WFFRC; https