We met at DS&AI Madrid meeting. I was the the English bloke who works in clinical trials.

Part of the Clinical Trial Technology and strategy group. Bringing new technology and services to our organisation

I met Jesus during the Bayer Data Science & Artificial Intelligence, DS&AI, F2F event in Madrid in May 2023. Jesus works at Bayer AG currently as the Head of Business Disruption. If you are into Stranger Things, Breakthrough Innovations, AcceleRed, TeamRed, Science4Berlin, STEM4Health, Hackathons, Biotech, Digital Health, Startups, Entrepreneurship, Intrapreneurship, Web3, Web5, Networking For Health, Science, Technology, Pharma, Exobiology, Space, Science Fiction, Germany, Cuba, you can connect with Jesus in LinkedIn: https://www.linkedin.com/in/yeysus/ Twitter: https://twitter.com/yeysus Meetup: https://www.meetup.com/members/45080772/ Web3: yeysus.eth/.tez/.near Some of his POAPs collections in Welook.io: Bayer: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/1 Corporates: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/2 Animated: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/5 Ladies: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/8 Beautiful: https://welook.io/0x74839F2fF3bb6F98E5f120329A76A89f52b95DCC/poap/c/9 Great connecting with you!

Our vision at Data Science Services & Solutions, DS3, is to Enable, Scale, and Operationalize R&D Data Science & AI capabilities to achieve Clinical Research and Development Speed, Efficiency, and Optimization. Learn more about our areas of responsibility, capabilities, strategic priorities, and collaborations. For more information, contact DS3 Head: Abi Velurethu. Artwork created using Stable Diffusion.

With the new head of R&D Community Engagement, RDCE, a new set-up has also been introduced, which newly regulates the tasks and responsibilities of the business partners assigned to the functions, SPOCs, which stands for Single Point of Contact. What is now in scope and what is not? The poster provides information on this.

The Applied Machine Learning Group (AML) strives for the application of a data-driven approach to drug research and development by developing and utilizing best-in-class machine learning (ML) models to optimize R&D processes. The implementation of ML algorithms accelerates drug discovery and a platform to monitor and self-train models enables portfolio view of our capabilities, allowing us to become more focused. We envision to work in a fast-paced setting, we expect to fail quickly and adapt swiftly, all while expanding your ML capabilities. We also believe in making the right choices not only for our immediate team but decisions to build solutions catered to broader R&D. The success at AML will be measured by bucketing the benefit of the developed capability into one or more of these three buckets, (1) Savings in time (2) Savings in cost (3) Generation of new insights