# Postdoctoral Position in AI-Driven Drug DesignPostdoc position·Post Doctoral·SwitzerlandPosition type: Postdoc postdoctoralLevel: Post DoctoralLanguage: English## About the PositionArtificial intelligence is rapidly transforming molecular design and drug discovery. However, the identification of successful drug candidates requires more than generating molecules with high predicted affinity: selectivity, physicochemical properties, potential adverse effects, synthetic accessibility, and experimental feedback must be considered simultaneously.Our research in the Computational Pharmacy group at the University of Basel focuses on developing next-generation AI approaches for drug design by combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: positionA fully funded Postdoctoral position is available in the Computational Pharmacy group at the University of Basel within an international Innosuisse research project on AI-driven closed-loop drug discovery.The project aims to establish an integrated Design–Make–Test–Analyze (DMTA) platform combining generative AI, ultra-large synthetically accessible chemical spaces, physics-informed molecular representations, off-target prediction, and experimental feedback. The developed methods will be applied in iterative prospective drug-discovery cycles, with a serine protease from the complement system serving as a real-world lead-optimization case study.The successful candidate will play a central role in the computational and AI components of the project and work closely with our international and industrial project partners.You will be responsible for:Developing and adapting machine-learning approaches for structure-based and generative molecular design.Integrating physicochemical information, including protein–ligand interaction features, into generative AI workflows.Developing computational workflows for closed-loop DMTA cycles in which experimental affinity, selectivity, and molecular-property data are continuously used to improve the next generation of proposed molecules.Applying and validating the developed approaches prospectively in the design and optimization of serine protease inhibitors.Collaborating closely with computational scientists, chemists, and biologists within the international project consortium.Contributing to scientific publications, presentations, and project reporting.Your profilePhD in Computational## Other Requirements & Additional InfoEmployment type: FULL\\_TIME
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Postdoctoral Position In Ai-driven Drug Design in Basel Arbeitgeber: ScholarLink Inc.
Die Technische Universität Ilmenau bietet als Arbeitgeber eine inspirierende Umgebung für wissenschaftliche Mitarbeiter*innen, die sich in einem dynamischen Team engagieren möchten. Mit einem klaren Fokus auf internationale Forschung und qualitativ hochwertige Lehre fördert die Fakultät für Wirtschaftswissenschaften und Medien nicht nur die persönliche und akademische Entwicklung ihrer Mitarbeitenden, sondern bietet auch zahlreiche Möglichkeiten zur Zusammenarbeit mit externen Partnern. Die offene und unterstützende Arbeitskultur sowie die Möglichkeit zur Promotion machen diese Position besonders attraktiv für alle, die eine bedeutungsvolle Karriere im akademischen Bereich anstreben.
