7.7 million female scientists and engineers in the EU

 In 2023, there were 7.7 million female scientists and engineers in the EU, 381 200 more than in 2022.

Across all economic activities present in the statistical classification of economic activities in the EU (NACE rev. 2), women represented 41.0% of the scientists and engineers workforce. This share was higher in services related activities at 45.6%. In manufacturing, women represented 22.4% of scientists and engineers, while in other activities that share was 23.9%. 

Among the EU countries, the proportion of female scientists and engineers varied widely in 2023, with the highest shares registered in Denmark (50.8%), Spain (50.0 %,) and Bulgaria (49.1%), Latvia and Ireland (each 49%). The lowest representation of female scientists and engineers was in Hungary (30.7%), followed by Finland (31.4%), Italy (34.1%), and Slovakia and Malta (each 34.3%).






At level 1 of the Nomenclature of Territorial Units for Statistics (NUTS 1), female scientists and engineers were in the majority in 12 EU regions:

_____________________________________________________________________________________________________________

More info:
Website link: https://databasescientist.org/
Contact us: contact@databasescientist.org
Nomination Link: https://databasescientist.org/award-nomination/?category=Awards&rcategory=Awardee

_______________________________________________________________________________________________________________ social media:
Twitter: https://x.com/databasesc10061
Pinterest: https://in.pinterest.com/databasescientist/
Linked in: https://www.linkedin.com/in/databasescientist-database-440a12365/
Instagram Link: https://www.instagram.com/databasescientist/













Comments

Post a Comment

Popular posts from this blog

Large Language Models and Vector Databases for News Recommendations

Image
  Large Language Models   (LLMs) generated a global buzz in the machine learning community with recent releases of generative AI tools such as Chat-GPT, Bard, and others alike. One of the core ideas behind these solutions is to compute a numerical representation of unstructured data (such as texts and images) and find similarities between these representations. However, taking all of these concepts into a production environment has its own set of machine learning engineering challenges: How to generate these representations quickly? How to store them in a proper database? How to quickly compute similarities for production environments? In this article, I introduce two open-source solutions that aim to solve these questions: Sentence Transformers  [1] : an embedding generation technique based on textual information and; Qdrant : a vector database capable of storing embeddings and providing an easy interface to query them. These tools are applied to NPR [2], a News Portal R...
Read more

Is Palantir creating a national database of US citizens?

Image
According to its website, Palantir makes "products for human-driven analysis of real-world data." On May 30, 2025,  The New York Times published an article   titled "Trump Taps Palantir to Compile Data on Americans," detailing a supposed combined effort between the U.S. federal government and the data software company Palantir to centralize data on American citizens. Data privacy advocates did not take the news well, calling it "dystopian" and a massive invasion of privacy. Four days later, Palantir posted a statement to X responding to the article, calling the reporting " blatantly untrue" because "Palantir never collects data to unlawfully surveil Americans, and our Foundry platform employs granular security protections." On June 9, 2025, the company followed up with a long blog post on X titled " Correcting the Record: Responses to the May 30, 2025 New York Times Article on Palantir," which aimed to fact-check the article....
Read more

NIH autism database announcement raises concerns among researchers

Image
A new research initiative from the U.S. National Institutes of Health (NIH) seeks to gather and analyze multiple autism-related datasets to better understand the underlying causes of the condition. Letters of intent are due tomorrow, but the project’s atypical call for applications has autism scientists divided on whether or not to participate. The Autism Data Science Initiative provides $50 million for an anticipated 10 to 25 projects, according to the 27 May announcement. The funding opportunity uses an Other Transaction (OT) funding mechanism, which tends to be implemented when, among other reasons, a project is expected to evolve over time, more collaboration is required from the NIH or nontraditional research groups are involved, according to an NIH website. For a field that has recently seen budget cuts, some researchers are welcoming the opportunity for funding, says   Helen Tager-Flusberg , director of the Center for Autism Research Excellence at Bosto...
Read more