Associate Principal Scientist - Cheminformatics

AstraZeneca GmbH; Mölndals kommun; On-site; SEK 900,000 - 1,200,000; Full time

Job summary

AstraZeneca GmbH in Gothenburg, Sweden seeks a Chemoinformatician (Associate Principal Scientist) to advance computational chemistry across discovery. You will work with machine learning, medicinal chemistry and multi-disciplinary teams to design data pipelines, predictive models, library design and SAR analysis to improve potency, selectivity and ADMET properties.

You will contribute to capability building, publish research, and collaborate with AZ sites and external partners, using HPC

Qualifications

• PhD (or equivalent) in computational chemistry, chemistry, pharmacology, or related field.
• Deep knowledge in ML and DL, esp. generative design, QSA/PR or reaction prediction.
• Strong experience applying ML/AI in drug discovery, esp. ligand-based design techniques.
• Knowledge of scientific computing and programming (Python, Perl, C, C++, Java, R); cheminformatics toolkits (RDKit, OpenEye); ML frameworks (scikit-learn, PyTorch, TensorFlow).
• Strong written and verbal communication skills and ability to collaborate in multidisciplinary project teams.
• Excellent time management and delivery focus.

Responsibilities

• Apply computational chemistry and AI to design, data pipelines, predictive models, library design and SAR analysis to improve potency, selectivity, activity and ADMET.
• Collaborate across AZ sites and with external partners; contribute to capability building and publish in peer‑reviewed journals.
• Work with a large community of computational chemists, train and deploy ML models on HPC clusters, and explore generative design and reaction predictions.

Skills

ML/DL in drug discovery

Ligand-based design

Programming & scientific computing

Education

PhD in computational chemistry or related field

Tools

RDKit

OpenEye

Python

C/C++

Java

Job description

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:

• 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-2026

Closing Date

09-aug.-2026

Our 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.