Data Science & AI Innovation Postdoctoral Fellow in Machine Learning for Chemical Synthesis and[...]

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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. /p pThe 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 research is expected to result in high‑impact publications and contribute to accelerating the Design‑Make‑Test‑Analyze cycle in active drug discovery projects. /p h3Why Join the Program? /h3 pThe 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. /p pPostdoctoral Research Fellows benefit from: /p ul liGuidance from accomplished scientific leaders and subject matter experts /li liAccess to advanced technologies, platforms, and research capabilities /li liCollaboration across disciplines and organizational boundaries /li liA global and diverse community of postdoctoral fellows /li liDedicated programming designed to help fellows thrive throughout their careers. /li liPersonalized 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. /li liOpportunities to present research, publish in leading journals, and build an international scientific network /li /ul h3Reimagining Medicine Together /h3 pAt 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. /p h3Key Responsibilities /h3 ul liAnalyze large‑scale chemical reaction datasets from proprietary and public sources to identify trends, opportunities, and challenges in chemical synthesis. /li liDevelop, implement, and evaluate machine learning models for predicting reaction success, reaction conditions, yield, regioselectivity, and molecular reactivity. /li liBenchmark state‑of‑the‑art AI approaches, including graph neural networks, transformer models, and foundation models, against relevant synthesis prediction tasks. /li liInvestigate novel pre‑training strategies leveraging large‑scale chemistry and physics‑based datasets to improve predictive performance and generalization. /li liCollaborate closely with medicinal chemists, synthetic chemists, and automation experts to address real‑world drug discovery challenges. /li liApply predictive models to enable broader substrate scope exploration, reaction optimization, and library synthesis design. /li liExplore integration of synthesis prediction models with generative chemistry and AI‑driven molecular design workflows. /li liPresent research findings internally and externally, publish in leading scientific journals, and contribute to the broader scientific community. /li /ul h3Essential Requirements /h3 ul liPhD 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). /li liDemonstrated record of scientific achievement (publications, presentations, patents, or equivalent) /li liDemonstrated experience developing and applying deep learning methods to scientific or chemical datasets. /li liStrong 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. /li liExperience with data analysis, statistical modeling, and handling large, complex datasets. /li liStrong commitment to learning, innovation, and professional development /li liAbility to work effectively in highly collaborative, multidisciplinary research environments. /li liExcellent communication skills and ability to present complex scientific concepts to diverse audiences. /li /ul h3Desirable Requirements /h3 ul liExperience 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. /li liExperience designing and querying relational databases or other structured data systems for scientific data management and large‑scale analytics. /li /ul h3Important /h3 pPlease submit your CV and cover letter by July 15, 2026 end of day. /p pIn your cover letter, please describe your research interests, career aspirations, and how participation in the Novartis Biomedical Research Postdoctoral Fellowship Program will support your long‑term development. /p pThe start date for the 2026 Novartis BR Postdoctoral Fellowship Program cohort is October 1, 2026. ppbSalary Range: /b CHF 0.00 - CHF 0.00 /p h3Job Description Summary /h3 pThis 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.br/Location: Basel, Switzerlandbr/Duration: 3 yearsbr/Program start date: October 1, 2026br/Application deadline: July 15, 2026 EOB /p h3Job Description /h3 pWe 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. /p pAs 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. /p pOur fellows are empowered to ask bold scientific questions, apply cutting‑edge technologies, and develop approaches that have the potential to transform patient care. /p h3Research Opportunity /h3 pJoin 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.

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.

Please confirm your availability to meet this start date in your cover letter. /p pPlease note that we can only accept applicants who are eligible to work in Switzerland. /p /p #J-18808-Ljbffr