Data Science & AI Innovation Postdoctoral Fellow in Machine Learning for Chemical Synthesis and Reactivity Prediction

ph3Data Science AI Innovation Postdoctoral Fellow in Machine Learning for Chemical Synthesis and Reactivity Prediction /h3h3Summary /h3pThis postdoctoral fellowship offers a unique opportunity to advance the use of artificial intelligence and machine learning for chemical synthesis and reactivity prediction in drug discovery. The successful candidate will develop and apply state-of-the-art predictive models using large-scale reaction datasets to improve chemical decision-making, reaction optimization, and molecular design, while collaborating with experts across data science, computational chemistry, medicinal chemistry, and synthesis technology. The project aims to accelerate the Design-Make-Test-Analyze cycle and contribute to next-generation AI-powered approaches for discovering new medicines. Location: Basel, Switzerland Duration: 3 years Program start date: latest November 15, 2026 Application deadline: September 23, 2026 EOB /ph3About the Role /h3pWe are excited to invite applications for the Novartis Biomedical Research Postdoctoral Fellowship Program; a unique training opportunity designed for exceptional early-career scientists eager to tackle some of the most challenging problems in biomedical research and drug discovery. As a Postdoctoral Research Fellow, you will join Global Discovery Chemistry in Basel and pursue an innovative research project at the forefront of biomedical science and drug discovery. You will work alongside leading scientists in a highly collaborative, multidisciplinary environment while gaining exposure to the broader ecosystem that translates scientific discovery into medicines. Our fellows are empowered to ask bold scientific questions, apply cutting-edge technologies, and develop approaches that have the potential to transform patient care. The Novartis Biomedical Research Postdoctoral Fellowship Program is designed to develop the next generation of scientific leaders, powering the future of medicine, through rigorous research, and immersive learning experiences, such as implementation of AI tools in biomedical research. /ph3Research Opportunity /h3pJoin an interdisciplinary research project at the intersection of artificial intelligence, machine learning, and synthetic chemistry. This fellowship aims to develop next-generation machine learning approaches that predict chemical reaction outcomes, reaction conditions, and molecular reactivity using large-scale proprietary and public reaction datasets. By leveraging more than two decades of reaction knowledge generated within Novartis, the fellow will investigate how modern AI methods, including graph neural networks, transformer architectures, and foundation models, can improve the efficiency and success rate of chemical synthesis. The project will focus on building predictive models that help chemists design more efficient synthetic routes, identify optimal reaction conditions, and expand access to diverse chemical space. The fellow will collaborate closely with experts in data science, computational chemistry, medicinal chemistry, and synthesis technology, with opportunities to integrate predictive chemistry models into generative AI workflows and emerging laboratory automation platforms. The research is expected to result in high-impact publications and contribute to accelerating the Design-Make-Test-Analyze cycle in active drug discovery projects. /ph3Why Join the Program? /h3ulliGuidance from accomplished scientific leaders and subject matter experts /liliAccess to advanced technologies, platforms, and research capabilities /liliCollaboration across disciplines and organizational boundaries /liliA global and diverse community of postdoctoral fellows /liliDedicated programming designed to help fellows thrive throughout their careers /liliPersonalized experiential learning opportunities through a Postdoc Practicum that empower fellows to explore new scientific domains, build cross-functional expertise, and expand their impact beyond their primary research project /liliOpportunities to present research, publish in leading journals, and build an international scientific network /liliWe are entering a new era of biomedical research breakthroughs through the convergence of biology, technology, and artificial intelligence tools, and fellows are also supported in engaging with these emerging approaches /li /ulh3Reimagining Medicine Together /h3pAt Novartis, our purpose is to reimagine medicine to improve and extend people-s lives. Through this program, you will grow as a scientist and future leader while contributing to discoveries that may ultimately benefit patients worldwide. /ppPlease note that we can only accept applicants who are eligible to work in Switzerland. /ph3Key Responsibilities /h3ulliAnalyze large-scale chemical reaction datasets from proprietary and public sources to identify trends, opportunities, and challenges in chemical synthesis /liliDevelop, implement, and evaluate machine learning models for predicting reaction success, reaction conditions, yield, regioselectivity, and molecular reactivity /liliBenchmark state-of-the-art AI approaches, including graph neural networks, transformer models, and foundation models, against relevant synthesis prediction tasks /liliInvestigate novel pre-training strategies leveraging large-scale chemistry and physics-based datasets to improve predictive performance and generalization /liliCollaborate closely with medicinal chemists, synthetic chemists, and automation experts to address real-world drug discovery challenges /liliApply predictive models to enable broader substrate scope exploration, reaction optimization, and library synthesis design /liliExplore integration of synthesis prediction models with generative chemistry and AI-driven molecular design workflows /liliPresent research findings internally and externally, publish in leading scientific journals, and contribute to the broader scientific community /li /ulh3Essential Requirements /h3ulliPhD in Data Science, Computer Science, Machine Learning, Cheminformatics, Computational Chemistry, Chemistry, Pharmaceutical Sciences, or a related quantitative discipline completed prior to the fellowship start date. The program is intended for scientists immediately following their PhD training (graduated in 2026). /liliDemonstrated record of scientific achievement (publications, presentations, patents, or equivalent) /liliDemonstrated experience developing and applying deep learning methods to scientific or chemical datasets /liliStrong programming skills in Python and familiarity with modern machine learning frameworks and architectures, such as graph neural networks, transformers, large language models or foundation models for scientific applications /liliExperience with data analysis, statistical modeling, and handling large, complex datasets /liliStrong commitment to learning, innovation, and professional development /liliAbility to work effectively in highly collaborative, multidisciplinary research environments /liliExcellent communication skills and ability to present complex scientific concepts to diverse audiences /li /ulh3Desirable Requirements /h3ulliExperience curating, processing, and analyzing large-scale chemical reaction datasets, including reaction encoding, atom mapping, reaction classification, and extraction of chemical knowledge from structured or unstructured data sources /liliExperience designing and querying relational databases or other structured data systems for scientific data management and large-scale analytics /li /ulh3Job Details /h3pJob ID REQ- /ppFull time Employment Type Early Career (Fixed Term) /ppShift Work No Others /ppDivision Biomedical Research Business Unit Research Location Switzerland Site Basel (City) Company / Legal Entity C028 (FCRS = CH028) Novartis Pharma AG Functional Area Others /p /p #J-18808-Ljbffr