{"id":7119,"date":"2023-09-18T20:25:17","date_gmt":"2023-09-19T00:25:17","guid":{"rendered":"https:\/\/ptp.cloud\/?post_type=ajde_events&p=7119"},"modified":"2024-08-22T19:06:49","modified_gmt":"2024-08-22T23:06:49","slug":"ai-driven-computational-drug-discovery-immersion-day-part-1","status":"publish","type":"ajde_events","link":"https:\/\/ptp.cloud\/events\/ai-driven-computational-drug-discovery-immersion-day-part-1\/","title":{"rendered":"AI-driven Computational Drug Discovery Immersion Day – Part 1"},"content":{"rendered":"

Part 1: 2023 Generative AI Immersion Series for HCLS Startups<\/strong><\/p>\n

AI-driven computational drug discovery has been a key player in lowering the cost and speeding up the timeline for drug development.<\/p>\n

Join your peers from leading startups as well as AWS Machine Language experts on September 26 for a virtual workshop focused on building ML\/HPC workloads to run protein folding\/design algorithms like AlphaFold. You will also hear from AWS Partner PTP as well as customers about leveraging AWS to deploy these workloads.<\/p>\n

This workshop is intended for technical stakeholders such as Heads of Computational Biology\/Chemistry, CTOs, Heads of Science\/Chief Science Officers. In this workshop, you will use AWS cloud services to predict protein structure and function. First, you will use Amazon SageMaker Studio to explore protein data. Next, you will experiment with machine learning algorithms to predict molecular properties. Finally, you will build high-throughput pipelines for protein analysis. Participants will leave this workshop with hands-on knowledge of the most advanced protein analysis workflows available today. You will need your laptop to follow along, but having your AWS account set up prior to the session is not necessary.<\/p>\n

Please sign up today to guarantee your spot!<\/p>\n

Agenda<\/strong>
\n10:00 \u2013 10:30 am ET: GenAI potential in Computational Drug Discovery (Amrita Sarkar)
\n10:30 \u2013 12:00 pm ET: AI-driven protein analysis on AWS (Experiment with protein folding and design in SageMaker Studio) with Sergey Menis
\n12:00 \u2013 1:30 pm ET: Distributed training of protein folding models using self-managed Frameworks. ML Frameworks workshop (Shubha Kumbadakone and Ankur Srivastava)
\n1:30 \u2013 2:30 pm ET: Partner session by Aaron Jeskey at PTP (Optimizing pipelines and sharing HPC case study)
\n2:30 \u2013 3:30 pm ET: Customer session
\n3:30 \u2013 3:35 PM ET: Survey, follow-up and closing remarks<\/p>\n

RSVP HERE<\/strong><\/a><\/h2>\n

Enhance your AI projects with our DevOps solutions. Visit our DevOps page<\/a> for more information.<\/p>\n<\/span>","protected":false},"author":2,"featured_media":10515,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"Part 1: 2023 Generative AI Immersion Series for HCLS Startups<\/strong>\r\n\r\nAI-driven computational drug discovery has been a key player in lowering the cost and speeding up the timeline for drug development.\r\n\r\nJoin your peers from leading startups as well as AWS Machine Language experts on September 26 for a virtual workshop focused on building ML\/HPC workloads to run protein folding\/design algorithms like AlphaFold. You will also hear from AWS Partner PTP as well as customers about leveraging AWS to deploy these workloads.\r\n\r\nThis workshop is intended for technical stakeholders such as Heads of Computational Biology\/Chemistry, CTOs, Heads of Science\/Chief Science Officers. In this workshop, you will use AWS cloud services to predict protein structure and function. First, you will use Amazon SageMaker Studio to explore protein data. Next, you will experiment with machine learning algorithms to predict molecular properties. Finally, you will build high-throughput pipelines for protein analysis. Participants will leave this workshop with hands-on knowledge of the most advanced protein analysis workflows available today. You will need your laptop to follow along, but having your AWS account set up prior to the session is not necessary.\r\nPlease sign up today to guarantee your spot!\r\n\r\nAgenda<\/strong>\r\n10:00 \u2013 10:30 am ET: GenAI potential in Computational Drug Discovery (Amrita Sarkar)\r\n10:30 \u2013 12:00 pm ET: AI-driven protein analysis on AWS (Experiment with protein folding and design in SageMaker Studio) with Sergey Menis\r\n12:00 \u2013 1:30 pm ET: Distributed training of protein folding models using self-managed Frameworks. ML Frameworks workshop (Shubha Kumbadakone and Ankur Srivastava)\r\n1:30 \u2013 2:30 pm ET: Partner session by Aaron Jeskey at PTP (Optimizing pipelines and sharing HPC case study)\r\n2:30 \u2013 3:30 pm ET: Customer session\r\n3:30 \u2013 3:35 PM ET: Survey, follow-up and closing remarks\r\n

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