Machine Learner, Bioinformatician, Pythonist. AMA!

The Data Assets and Insights Solutions subfunction, DAIS, consists of a team of dedicated computer and data scientists which combine deep R&D process and domain expertise (biology, chemistry, pharmacy, etc) with advanced computational expertise (software engineering, natural language processing, scalable architectures, bio- & chem-informatics, data integration & visualization, etc). We integrate, enrich and harmonize large scientific datasets to build foundational data assets which are used by the R&D organization and our team to build insights solutions. They address key R&D challenges to improve speed, quality and probability of success of our R&D pipeline. Selected business critical tasks within R&D we are focusing on: - Target identification including holistic assessment - Disease understanding including precision medicine - Pipeline evaluation (therapeutic potential and risks) - Modality selection including identification of tool compounds - Identification of collaboration and in-licensing opportunities For more information contact: Wolfgang Thielemann. Artwork: Licensed pictures.

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!

Experienced leader in development, validation, and implementation of clinical trial software and processes

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

Morphological profiling with Cell Painting allows an unbiased characterization of cellular states by observing changes in cell morphology. Cell Painting images are information-rich and can guide the elucidation of mode of action, toxicity, and off-target effects, help drug repurposing, indicate differentiation states of iPSC lines, discover new biology and more. However, this technology is data-greedy and computationally complex and demanding. At DS&AI, we enable this technology at Bayer! To this end, we support large data generation campaigns internally and externally, develop novel machine learning algorithms, and create tools for efficient analysis and visualization of Cell Painting data. For more information please contact Paula Marin Zapata or Marc Osterland. Self-painted image modified using pictures from https://quizlet.com/420027050/animal-cell-diagram/ as starting models.