Best links of the week #62

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Best links of the week from 23rd March to 29th March

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Links

  1. Share Code from any Device.
  2. How Fast Does a Virus Spread? Let’s Do the Math at WIRED.
  3. The Promising Math Behind ‘Flattening the Curve’ at WIRED.
  4. SAS libera mais de 100 cursos online de análise de dados at CanalTech.
  5. Dashboard do Ministério da Saúde para a COVID-19.
  6. Dashboard do governo Frânces para a COVID-19.
  7. How many tests for COVID-19 are being performed around the world? at Our World in Data.
  8. Corona Data Scraper.
  9. Why the ‘gold standard’ of medical research is no longer enough at statnews.
  10. Coughona: Identifying Coronavirus based on cough noise.
  11. Graph theory suggests COVID-19 might be a ‘small world’ after all at ZDNet.
  12. Case control study by Timiresh Das at SlideShare.

Blog posts

  1. Healthdata e Evidências de Machine Learning na saúde by Fabiano Filho at E-Health: healthtechs e healthdata.
  2. Um checklist para machine learning, e nada mais que isso by Fabiano Filho at GELEIA.
  3. March ’20 Community Gems (DVC Tips) at DVC Blog.
  4. How to create a simple Coronavirus dashboard specific to your country in R at Stat and R.
  5. Por que ficar em casa? at DataSciBR.
  6. Introduction to Bayesian Decision Theory at Towards Data Science.
  7. Coronavírus: não nos deixemos enganar pelos nossos vieses at Fernando Malta’s LinkedIn.
  8. A matemática promissora por trás do ‘achatamento da curva’ at Portal Deviante.

Videos

  1. Introdução à Causalidade by eu 🙂 at EsTaTiDados’s YouTube channel.
  2. Entendendo o comportamento de uma doença at Júnior Koch’s YouTube channel.
  3. Why we randomize at Darren Dahly’s YouTube channel.
  4. Simulating an epidemic at 3Blue1Brown’s YouTube channel.
  5. Randomized Controlled Trials (RCTs) at UNICEF Innocenti’s YouTube channel.
  6. Epidemiology Study Types: Randomized Control Trial at daf189’s YouTube channel.

Positions available

  1. Data Scientist at Auto Avaliar.
  2. Cientista de Dados (Sênior) at PicPay.
  3. Four postdoctoral opportunities at UT Austin.
  4. Ph.D. position on “Light-weight Deep Learning for Visual Analysis” at Aarhus University.
  5. Ph.D. opportunities in Statistics, Mathematical Biology, and the mathematics of Insurance and Economics at the University of Copenhagen.
  6. Group leader positions ML in Science at Tubingen University.
  7. Postdoctoral researcher in AI and scientific manager of the Amsterdam ELLIS unit at the University of Amsterdam.
  8. Fully funded Ph.D. studentship for UK/EU students on Machine/Deep Learning Theory on Self-Supervised Learning and Variational Inference at the University of Aberdeen.
  9. 5-6 fully-funded Ph.D. scholarships in AI and ML for manufacturing at Aarhus University.
  10. Postdoctoral opportunity in Bioinformatics at EMBRAPA.
  11. Engenheir@ de Dados Sênior at tembici.
  12. Data Scientist at Accenture.
  13. Senior Data Scientist at IQVIA.
  14. Data Scientist – Advanced Analytics at IBM.
  15. Especialista Big Data at Semantix Brasil.
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