I've met Tilman at DS & AI F2F Madrid
Tilman is an automation manager, currently taking care of the reporting sub-stream in the Gemstone Ruby project.
What ever you do, do it with passion or et least with style! We in Medical Devices and eHealth stand for life changing combinations of medical devices together with our drugs. Iยดm proudly presenting the eHealth & Medical Software Solution team. Our joint vision is that every patient should get access to break trough eHealth solutions. Come and visit us - go/MDeH - or connect with me via Linkedin. Always keen to chat about "AI applied in med tech", "data mech in clinical practice", "if compliance and agility can coexist" & "how to get form a research hypothesis or concept to a data product"
Hi, I'm Lucas. Nice to meet you!! My passion is software engineering and music. Check out my band: https://www.excelsis-rockband.de/
Work in CTTS (Clinical Trial Technology Strategy). Was part of Clinical Operations where I worked in Data Driven Feasibility and recently co-led the initiatives for DCT. Work with Academic Institutions and external innovative companies from start up, large blue chip companies to top 5 tech companies.
I've met Karen Geffert at DS & AI F2F Madrid
Data Acquisition Technology Expert (Associate Director) at Bayer Healthcare Pharmaceuticals
I met Leonidas at Bayer's DS&AI Madrid 2023 global meeting
Thank you for the discussion during the global meeting. This token commemorates the occasion. DS3, Strategy & Venturing Major
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.
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
Head of Product Owner Hub - Portfolio & Operations