ERN CRANIO online annual meeting 2020
On 14 November 2020
At : Barcelona-Spain
On 14 November 2020
At : Barcelona-Spain
From 14 to 16 November 2020
At : Paris-France
From 27 to 28 November 2020
At : Brussels-Belgium
From 11 to 13 December 2020
At : Dusserldorf - Germany
From 07 to 08 January 2021
At : Pennsylvania - United States
On 05 November 2020
At : Berlin-Germany
From 15 to 17 January 2021
At : Paris-France
From 13 to 15 March 2021
At : Glasgow-Scotland
From 20 to 24 July 2021
At : Leiden - Netherlands
From 13 to 14 November 2021
At : Sydney-Australia
The FAIRplus Fellowship Programme is a training programme in FAIR data management. The FAIRplus programme is aimed at developing tools and guidelines for FAIR (Findable, Accessible, Interoperable, Reusable) life science data. Candidates should belong to a FAIRplus partner organisations. There are also limited places for applicants from outside FAIRplus progamme (small and medium size of enterprises). Interested candidates will apply by submitting a FAIRification project they will develop during the programme. The programme will start in April 2021, and will last 8 months.

Please send your CV and cover letter with the reference US14-2020-06 to:
• Annie OLRY
• E-mail : jobs.orphanet@inserm.fr
• Tel : +33 (0)1 56 53 81 37
Please send your CV and cover letter with the reference 2020-US14-001 to:
• Annie OLRY
• E-mail : jobs.orphanet@inserm.fr
• Tel : +33 (0)1 56 53 81 37
Please send your CV and cover letter with the reference 2020-US14-002 to:
• Annie OLRY
• E-mail : jobs.orphanet@inserm.fr
• Tel : +33 (0)1 56 53 81 37
Please send your CV and cover letter with the reference 2020-US14-001 to:
• Annie OLRY
• E-mail : jobs.orphanet@inserm.fr
• Tel : +33 (0)1 56 53 81 37
Please send your CV and cover letter to:
• Véronique KERLAN
• E-mail : veronique.kerlan@chu-brest.fr
• Tel : +33 (0) 2 98 34 71 19
The author makes a comparison between healthcare databases using natural language processing and search engines. 30 rare diseases and 500,000 search results were carried out using Pubmed, FindZebra, and the search engine Google. The same results were applied to common diseases, and the author concluded that FindZebra and Google provide good results in the case of common diseases as regards the evaluation of therapies and diagnosis. The quantity of findings from professional databases, for example from Pubmed, remains unsurpassed.