Congrats on befriending the seagull! Born on a rocky cliff overlooking the Atlantic Ocean, our seagull had always been drawn to the vastness of the sea. It was a peaceful life, but our seagull was destined for greater things. As it grew older, the seagull began to develop a keen interest in technology and, more specifically, the field of machine learning. It started to spend its evenings poring over scientific papers and online tutorials on the latest techniques and algorithms. And soon enough, it had become an expert on cutting-edge machine learning applications. But our seagull was no recluse. Despite its fascination with technology, it still loved a day at the beach, basking in the sun and watching the humans go about their business. It was here that it would often strike up conversations with the beachgoers, sharing its knowledge of machine learning and even offering advice on how to apply it to discovering new targets. Its story inspired many, and it remains a beloved figure in both the tech and beach communities. I'm sure that your encounter with the seagull will be a memory that you'll cherish for a long time to come!

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.

Nico Bernsmeier PhD, Head of Product Owner Modalities and CGT. Trained Molecular Biologist. Joined Bayer 14 years ago. I am passionate about bringing the digital world to the labs. I love the challenge of combining the scientifc aspiration of R&D with the hard reality of IT. Creating a work environement where our product teams can excel in driving their products forward is the challenge we face.

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!

At Language of Life, LoL, we combine state-of-the-art machine learning models, bioinformatics and expert knowledge to understand and design large biomolecules (RNA, DNA, Proteins), helping deliver the best drug, faster and cheaper, to address our patients’ needs. Our objectives are, 1) Drug the undruggable 2) Target any modality 3) Efficient Dry lab – Wet lab loops 4) Understand Patient & Disease

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