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Would you like to apply your expertise in an industry-leading pharmaceutical company to help shape the future of AI-assisted drug discovery? We invite applications for an Industrial PhD position at AstraZeneca, in collaboration with \u00c9cole Polytechnique f\u00e9d\u00e9rale de Lausanne (EPFL), as part of a Marie Sklodowska-Curie training network. The successful candidate will be placed within the Molecular AI department of Discovery Sciences, at AstraZeneca in Gothenburg, Sweden. The student will be enrolled as an external PhD student at EPFL. About the PhD project This PhD project is part of the doctoral training network LowDataML that consist of of 17 members across academic and industrial institutions in Europe. The vision of the network is to develop innovative machine learning technologies operating in the low data regime. The network will also apply these technologies in drug discovery for cancer, diabetes, and neurodegenerative diseases. The collaboration between AstraZeneca and EPFL is focused on developing agentic AI workflows based on large language models for complex decision making in drug discovery. The PhD project will work on fundamental aspect of such systems but also apply them to projects in AstraZeneca and the other member organizations. At AstraZeneca, the student will be part of Discovery Sciences that are applying word-leading expertise the support the identifications of targets and drug candidates. The PhD studies will be carried out in the MolecularAI department that are developing AI platfoms to accelerate early drug discovery. The department work on for instance molecular design, property predictions, physics-based modelling, synthesis planning, and agentic AI. Apart from building internal platforms, the department is host to more than ten industrial PhD candidates and postdocs that are having close collaborations with academic partners. The Laboratory of Artificial Chemical Intelligence (LIAC) at EPFL operates at the intersection of machine learning and the chemical sciences. LIAC is dedicated to developing and applying cutting-edge deep learning and natural language processing models to accelerate scientific discovery. We focus on fundamental challenges in chemistry and materials science, including automated retrosynthesis, reaction outcome prediction, de novo molecular design, and the development of large language models (LLMs) and agents. What you'll do? The major responsibilities for an industrial PhD student position include conducting doctoral research. The student will be expeted to plan, write, and publish high-quality scientific papers. By the end of the PhD, students will be capable of identifying novel research directions and design appropriate computational experiments to test valuable hypotheses. 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