Aug. 4, 2022, 1:10 a.m. | Daniele Brambilla (1), Davide Maria Giacomini (1), Luca Muscarnera, Andrea Mazzoleni (1) ((1) TheProphetAI)

cs.LG updates on arXiv.org arxiv.org

New powerful tools for tackling life science problems have been created by
recent advances in machine learning. The purpose of the paper is to discuss the
potential advantages of gene recommendation performed by artificial
intelligence (AI). Indeed, gene recommendation engines try to solve this
problem: if the user is interested in a set of genes, which other genes are
likely to be related to the starting set and should be investigated? This task
was solved with a custom deep learning …

arxiv bio deep learning gene learning recommendation recommendation engine

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US