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Best links of the week from 8th July to 14th July

Links

1. The “Rmd first” method: when projects start with documentation Sébastien Rochette’s GitHub repository.
2. goodpractice: Advice on R Package Building.
3. Sampling (statistics) at Wikipedia.
4. Bootstrapping (statistics) at Wikipedia.
5. Jackknife resampling at Wikipedia.
6. Bootstrap in R by Łukasz Deryło at DataCamp Tutorials.
7. How can I generate Bootstrap statistics in R? at the FAQ of the Institute for Digital Research & Education (UCLA).
8. How does R handle missing values? at the FAQ of the Institute for Digital Research & Education (UCLA).
9. How does R handle overlapping object names? at the FAQ of the Institute for Digital Research & Education (UCLA).
10. How can I test for contrasts in R? at the FAQ of the Institute for Digital Research & Education (UCLA).
11. Explaining to laypeople why bootstrapping works at Cross Validated.

Blog/posts

1. Exploring the gt package with the useR 2019 schedule at Citizen Statistician.
2. RStudio Cloud in the classroom at Citizen Statistician.
3. 47 New External Data Science / Machine Learning Resources and Articles at Data Science Central.
4. Kaggle survey 2018: Maps of programming languages used and repartition of reproducibility issues at StatnMap.
5. My 2 cents on the “R vs Python” squabble by R on Just be-cause at R-bloggers.
6. A Gentle Introduction to the Bootstrap Method at Machine Learning Mastery.
7. An Introduction to the Bootstrap Method by Lorna Yen at Towards Data Science.

Videos

1. Bootstrapping, a resampling method at Matthew E. Clapham YouTube channel.
2. Why Bootstrap? (Part 1), Bootstrap for One Mean (Part 2), General Steps to Bootstrap (Part 3), Bootstrap Confidence Intervals for a Difference in Two Means (Part 4), Bootstrap Confidence Intervals for Regression Coefficients (Part 5) and Characteristics of the Bootstrap Distribution (Part 6) at Professor Knudson YouTube channel.
3. Confidence Intervals: Intro to bootstrapping proportions at apethan
   YouTube channel.
4. Bootstrapping and resampling Part 1, 2, 3 and 4 at
   Brian Caffo‘s YouTube channel.

Positions available

1. Ph.D. Position in Bioinformatics: Identification of gene regulation mechanisms by integrative and massive analysis of sequencing data at INSERM.
2. Several Ph.D. scholarship opportunities at the University of Trento.
3. Postdoctoral researcher position in Applied Reinforcement Learning at the University of Antwerp.
4. Jobs for PostDocs & Ph.D. Students at the Swiss AI Lab, IDSIA.
5. Postdoctoral opportunities through the Pew Latin American Fellows at the Pew Charitable Trusts.
6. Post-doctoral position fellow on automatic machine learning at the Eindhoven University of Technology.
7. Director of Data Science at IDEO.
8. Cientista de Dados at BRT Intelligence.
9. Engenheir@ de Dados Lead at Social Miner.
10. Engenheir@ de Dados SR at Social Miner.
11. Programador Hadoop at Tivit.
12. Cientista de Dados at B2W Digital.
13. Data Engineer Specialist / Senior at Catho.
14. Professor(a) plataformas Cloud at Alura.
15. Analista de Big Data at Mirante Tecnologia.
16. Ph.D. in Integrated Biomedical Sciences at UT Health San Antonio.
17. Many Master of Science opportunities at UT Health San Antonio.
18. Research Associate in Next Generation Artificial Intelligence at the University of Sheffield.
19.  Postdoctoral Research Fellow on the project “Model Criticism in Multi-Agent Systems” at the University of Edinburgh.
20. Associate Professor of Natural Language Processing and Machine Learning at the University of Copenhagen.