Ph3Summary /h3 pJob Title: Director Group Head (Applied AI) /p pLocation: Basel, Switzerland /p pRelocation Support: This role is based in Basel, Switzerland. Novartis is unable to offer relocation support: please only apply if accessible. /p pNovartis has embraced a bold strategy to drive a company‑wide digital transformation. Our objective is to position Novartis as an industry leader by proactively adopting digital technologies that foster innovative approaches to hasten drug discovery and development. By utilizing internal and external RD data with the power of data science, predictive models, generative AI, and machine learning, we aim to identify new targets, create more effective therapeutic molecules, better predict drug pharmacokinetics and safety risks, refine clinical trial design, and significantly shorten development cycles. The AI4R team leads BR in exploring and applying advanced AI and ML methodologies to generate novel drug discovery insights and to speed and improve drug discovery efficiency while focusing on patients’ needs. /p pAI4R partners with drug discovery teams, raises the level of AI expertise across Biomedical Research (BR), and ensures that BR science keeps up with the rapidly evolving ecosystem of AI technologies by connecting with AI leaders in academia and industry. /p h3About The Role /h3 pAs Director Group Head (Applied AI), you will shape how advanced machine learning approaches accelerate drug discovery, translating complex data into meaningful scientific insights that can transform patient outcomes. You will lead high‑impact collaborations, guide strategic AI direction across research domains, and empower teams to push the boundaries of what is possible in developing better medicines, faster. /p h3Key Responsibilities /h3 ul liDefine and lead the applied artificial intelligence strategy and multi‑year roadmap across drug discovery research. /li liAlign priorities with portfolio needs, scientific opportunities, and measurable business and research impact. /li liLead multidisciplinary teams to identify, prototype, benchmark, and deploy fit‑for‑purpose artificial intelligence solutions. /li liGovern an applied artificial intelligence portfolio with clear intake, prioritization, resourcing, delivery oversight, and success metrics. /li liEstablish best practices for problem framing, data readiness, benchmarking, evaluation design, and reproducible model development. /li liDrive benchmarking of foundation and task‑specific models, enabling transparent trade‑offs and informed adoption decisions. /li liPartner with engineering teams to scale solutions and embed them into day‑to‑day scientific decision making. /li liDefine rigorous evaluation metrics linking model performance to downstream decisions and experimental outcomes. /li liBuild a culture of scientific rigor, rapid iteration, mentorship, and practical impact across teams. /li liForge strategic academic and industry collaborations to accelerate innovation, benchmarking, and technology transfer. /li /ul h3Essential Requirements /h3 ul liDemonstrated experience in leading core machine learning capability development initiatives across drug discovery teams and use cases. /li liProven experience with foundation model benchmarking in drug discovery applications. /li liHands‑on experience applying machine learning to core drug discovery areas such as target identification or computational chemistry. /li liStrong experience in large‑scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworks. /li liDeep curiosity and passion for biomedical sciences and therapeutic discovery, with ability to explain complex technical concepts clearly. /li liMinimum of 12+ years of experience in innovation, development, deployment, and continuous support of machine learning and modelling solutions. /li liStrong coding proficiency in Python and deep learning frameworks, with experience using version control systems such as Git. /li liAbility to manage complexity, balance priorities, and drive outcomes effectively within matrixed environments using a proactive mindset. /li /ul h3Desirable Requirements /h3 ul liPublications, patents, or open‑source contributions demonstrating machine learning innovation and domain expertise. /li liStrong curiosity for emerging technologies with pragmatic ability to apply them to real‑world business challenges. /li /ul h3Commitment to Diversity and Inclusion /h3 pNovartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. /p h3Accessibility and Accommodation /h3 pNovartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or to receive more detailed information about the essential functions of a position, please email and share the nature of your request along with your contact information. Please include the job requisition number in your message. /p /p #J-18808-Ljbffr