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Field
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. · Familiarity with data analysis pipelines within R or similar computational language. · Strong writing and oral communication skills. · Excellent analytical thinking and creative troubleshooting skills
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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to Kiran R. Patil (kp533@mrc-tox.cam.ac.uk ) If you have any queries regarding the application process, please contact hradmin@mrc-tox.cam.ac.uk Further information can be found on our website: https
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skills for this position. Specifically, the PA will use generalized additive mixed-effects models to analyze data from existing and ongoing projects. Fluency with the R programming language is essential
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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interpretation. A Ph.D. in biostatistics, statistics, bioinformatics, computational biology, or computer science is required. Strong computational background with programming and visualization skills in R and
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of Surrey, University of Leeds, UKCEH) and Chile (Universidad de Desarrollo and MICROB-R). You will use a system modelling approach to a) quantify available data, b) knowledge gaps and associated risks to c
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businesses use self-regulation (S-R) to influence public opinion and preempt statutory regulation. The postdoctoral researcher will primarily contribute to Work Package 1 (WP1), which focuses on survey
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GSMI - Postdoctoral Researcher - Plant Ecology and Soil-Plant Interactions in Vegetated Photovoltaic
data analysis (R, multivariate statistics). Experience in GIS. Strong scientific writing skills and command of scientific English. Initiative and autonomy to conduct fieldwork. Application Documents
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machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical