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Field
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knowledge of basic techniques in molecular biology. Working knowledge of R and Python programming environments. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5284-FABLEG-002
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collaboration with Growgraph, an R&D startup engaged in advancing knowledge graph technologies and AI-driven methods for structured data analysis. This partnership aims to foster the transfer of research outcomes
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
stream chemistry data collected across a network of sites. The position will require downloading of data of field instruments and shared data repositories, and the development of code (R or Python based
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This opportunity is open to candidates of any nationality. The selected candidate will receive a FAPESP Post-Doctoral fellowship in the amount of R$ 12,570.00 monthly and a research contingency fund, equivalent
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. He/she will need to master data processing software such as R. The candidate is also expected to be curious and imaginative, to challenge the team by proposing radically different approaches
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-postdocIBSoFACTo@emploi.beetween.com Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Skills/Qualifications Practical experience with bioinformatics tools (R, Python, etc.) is required
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application of statistical software, preferably R, STATA Good knowledge of national and international clinical research regulations (e.g. HFG, ICH-GCP) Excellent written and oral communication skills in German
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in MATLAB/Python/R are desirable but not required. The position is part of a well-funded research program and will provide the opportunity to produce high-impact publications and establish
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requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position
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Engineering, or related. Strong experience in ODE/PDE modeling and simulation (MATLAB, Python, or R). Experience withnumerical methods, optimization, parameter estimation, and sensitivity and uncertainty