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-tests, nonparametric tests, power analyses, multivariate and/or ordination techniques. Demonstrable knowledge in a programming language or languages often applied to environmental datasets; examples could
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skills. Personal and relational qualities will be emphasized. Research experience, ambitions and potential will also count when evaluating the candidates. Special requirements for the position
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, nearly 12,000 faculty and staff and 350,000+ living alumni, UC combines a Top 35 public research university with a physical setting The New York Times has called “the most ambitious campus design program
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or ancestral recombination graphs. You have experience in a high-level programming language. You are interested in developing open-source software for academic and applied work. You are independent, organised
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research into the dynamics and prediction of the Western Central Pacific as part of the collaboration between the IMOS FishSOOP programme (run through UNSW) and the Pacific Community. The position will use
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experiments would also be preferred. Proficiency in programming for experiments using z-tree and (or) o-Tree/Python would be necessary. Some knowledge of web development languages (HTML, CSS, Javascript) would
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). The salary for this post is £40,497 to £48,149 per annum. Your skills and attributes for success: The ability to use mainstream data science programming languages (such as R and Python) for data extraction
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Requirements: PhD degree in physics, engineering or related field. Familiarity with electrodynamics and electromagnetism. Good written and oral communication skills. Proficiency in scientific programming e.g., C
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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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) proficiency in programming languages such as Perl, C, or Python; 2) experience with bioinformatics tools and platforms, such as GATK, BLAST, deepvariant, samtools, etc.; 3) familiarity with statistical analysis