Associate Principal Scientist - Cheminformatics
Join a world leading team in developing the next generation of small molecule and PROTACs medicines! AstraZeneca R&D, Gothenburg, Sweden seeks to recruit a Chemoinformatician into Computational Chemistry, BioPharma Chemistry within Discovery Sciences.
AstraZeneca is committed to the development of the next generation of innovative medicines. The Computational Chemistry team are using of state of the art in silico methods for molecular modelling, ligand design, property predictions and data analysis as an integral part of BioPharma drug discovery projects with a focus on small to medium sized molecules. The team operates in a highly cross disciplinary environment in close collaboration with scientists from the Chemistry, Translational, Bioscience, DMPK, Molecular AI and Pharmaceutical Sciences departments to advance the BioPharma project pipeline.
What you’ll do:As a Chemoinformatician (Associate Principal Scientist) you will have a profound impact on multiple projects across the BioPharma portfolio. You will work collaboratively with machine learners, medicinal chemists and multidisciplinary teams across all discovery phases. You will efficiently and proactively apply a full range of computational chemistry and AI approaches to deliver data pipelines, design, predictive models, library design and SAR-analysis to improve potency, selectivity, activity and/or ADMET properties of our drug compounds.
You will identify scientific improvement areas in computational sciences and contribute to capability building by collaborating with external partners and colleagues across AZ sites. In parallel, assess how these advances apply to AstraZeneca projects and help implement them in active programs.The role offers opportunities to publish original research and reviews in peer reviewed journals and requires maintaining up to date awareness of the literature and developments in the field.
You’ll work alongside a large community of computational chemists across functions – spanning cheminformatics, molecular simulations, structure and ligand based design, machine learning and model development – in a collaborative, cross disciplinary environment. You’ll also have access to shared high‑performance compute clusters and state‑of‑the‑art software and pipelines to train and deploy machine learning models, work with generative design, co-folding up to synthesizability and reaction predictions.
Essential requirements:We are seeking an engaged chemoinformatician with a solid knowledge of drug discovery concepts and a proven track record of applying computational/machine learning techniques with measurable impact on drug discovery project delivery. The candidate is expected to have a deep understanding of how computational chemistry contributes to drug discovery projects together with a good knowledge of the drug discovery process including other disciplines, such as synthetic, structural and medicinal chemistry, DMPK, structural biology, biophysics, biological science etc.
More specifically you have:
PhD (or equivalent experience) in computational chemistry, chemistry, pharmacology, or a related field with a strong computational background
Deep knowledge in machine learning and deep learning techniques, especially regarding generative design, QSA/PR or reaction prediction.
Strong experience in the application of ML/AI in drug discovery specifically with ligand-based design techniques.
Knowledge in scientific computing, and programming skills (e.g. Python, Perl, C, C++, Java, R), cheminformatics toolkits (e.g. RDKit, OpenEye), data standards (e.g. SMILES/SMARTS, InChI, SDF), ML frameworks (e.g. scikit learn, PyTorch/TensorFlow), cloud basics and agents.
Strong written and verbal communication skills and ability to collaborate in multidisciplinary project teams
Excellent time management skills, forward planning and delivery focus
Desirable requirements:
Experience in structure-based design, especially molecular dynamics and/or modern FEP methods.
Work policy:When we put people in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. This role is located in Gothenburg, Sweden and is not available for remote work or with travel or commuting support.
Why AstraZeneca?At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.
What's next:If this sounds like the place and role for you – apply today! We look forward to get to know you better! Welcome with your application no later than August 9, 2026.
Date Posted
16-juli-2026Closing Date
09-aug.-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.
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