CrowdDoing machine learning of medicinal foods effectiveness volunteer
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Recruiting Organization: M4A FOUNDATION - CROWDDOING
CrowdDoing machine learning of medicinal foods effectiveness volunteer help us to review data science pathways for medicinal foods evidence assessment. A poster about these opportunities can be seen here:
outcome effectiveness from peer to peer randomized RCTs medicinal foods development arc. CrowdDoing medicinal foods data science team aim to leverage public data to analyze co-variates with stress, anxiety, sleep and medicinal foods. We are also working towards a HIPPA compliant phase 2 that will let people test medicinal foods for themselves.
You can see an overview of our medicinal foods application here ( https://docs.google.com/presentation/d/12aEqwiRctIx3QcvK6HNFy4uJ5TgRffxQ7xPLEINNyJw/edit?usp=sharing). You can see a data science collection roadmap for how we can match million of recipe reviews to co-variates like stress and anxiety here: https://drive.google.com/file/d/1gF951Q7-XHFblTG-znjW3xXA8XAkPslB/view?usp=sharing. You can see a brake-down of human capital requirements for this project here: https://docs.google.com/document/d/1Kf3mIHQ9_YilBk9kBCvCFXaTj2AbA07SFAX_hv55Cik/edit?usp=sharing.
"To help support you joining the right part of CrowdDoing for you, please use this form: https://docs.google.com/forms/d/e/1FAIpQLSftd6E0tyV2uq7mMty1rZ80BB2MSGhbnof9gRBvaQXbrttIkg/viewform?usp=sf_link"
If you have any questions about processes for joining CrowdDoing.world as a volunteer to support our efforts in systemic change please write to firstname.lastname@example.org
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Fee Amount: None
This opportunity is recurring
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December 30, 2021
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