Research Software Consultant

About AstraZeneca

AstraZeneca is a global biopharmaceutical company dedicated to the discovery development and commercialisation of prescription medicines for some of the worlds most serious diseases. Beyond being one of the leading pharmaceutical companies globally were proud of an outstanding workplace culture that inspires innovation and collaboration. Employees are empowered to express different perspectives and feel valued energised and rewarded for their ideas and creativity. Weve been building and developing our technology to enable our transformation into a digital- and data-led enterprise. Theres never been a better time to join as we bring our digital strategy to life with huge opportunities to develop explore and thrive.

Join our Data Analytics & AI organisation in Gothenburg as a High-Performance Computing (HPC) Research Software Consultant where youll empower scientists with HPC to accelerate early-stage drug discovery. We particularly welcome candidates with experience in academic research environments those who have built or supported computational workflows in labs or core facilities collaborated on publications and taught or mentored researchers. Working in Technology here means taking ownership challenging the status quo and orchestrating new possibilities whether optimising sophisticated workflows collaborating at hackathons or pushing boundaries with large-scale data.

Based at our Gothenburg R&D site one of AstraZenecas strategic research hubs youll work in a truly global multinational environment where collaboration spans teams functions countries and even companies. With 2900 colleagues from 70 countries its an inspiring place where the history and advancement of scientific breakthroughs come together. Because we believe collaboration is essential to innovation we expect you to be on site on average at least three days per week to connect move at pace and challenge perceptions while balancing individual flexibility.

About the role

As a High-Performance Computing Research Software Consultant youll enable scientists to build improve and support computational workflows that drive high-impact science. The role blends hands-on problem solving workflow optimisation training and community building. You will collaborate with researchers and engineering groups to advance computational capabilities promote guidelines and strengthen a collaborative research computing community. Your background working with academic researchers translating experimental questions into robust reproducible computation will help you guide project teams from prototype to production-grade analysis.

About the team Scientific Computing Platform (SCP)

Within Data Analytics & AI (DA&AI) the Scientific Computing Platform delivers the high-performance computing foundations that power a broad range of fields across the early drug discovery pipeline including computational chemistry imaging multiomics structural biology data science and AI. We support both onpremises and cloudbased HPC environments and offer a rich ecosystem of open-source and commercial scientific software workflow tools and AI technologies. As a collaborative sciencefirst team we work closely with researchers and infrastructure development partners. We ensure our computing environments tools and services evolve with scientific needs so teams can focus on advancing their science.

Key responsibilities

• Guide researchers and developers in designing and improving computational workflows from exploratory prototypes to reproducible pipelines appropriate for publication and re-use.
• Optimise debug and document scientific applications and pipelines; champion reusable open and well-governed solutions across the organisation and research communities.
• Promote efficiency sustainability and reliability in computational pipelines; advocate for clear records version control testing and reproducibility best practices common in academic research.
• Deliver presentations contribute to research software engineering community efforts and engage with internal/external academic partners and consortia.
• Champion knowledge sharing and peer learning across user communities including training aligned to the needs of scientists and research groups.
• Collaborate with HPC support and platform engineering teams to align tools and software with evolving research needs and experimental designs.
• Develop and deliver engaging training coaching and technical onboarding for scientists and computational users; contribute to internal documentation and learning materials.

Essential requirements

• HPC & Linux: Strong expertise with HPC job schedulers and deploying/using scientific computing software on Linux in research settings.
• Programming & workflows: Experience developing scientific workflows or applications using Python R or shell scripting; working knowledge of parallel computing frameworks (e.g. MPI CUDA). Evidence of applying these skills to research questions.
• Research communication & collaboration: Ability to explain technical concepts clearly and collaborate with scientists across diverse domains; experience supporting academic labs core facilities or research consortia.
• Problem solving in research contexts: Demonstrated ability to diagnose and resolve issues in research computing environments balancing scientific validity performance and reproducibility.
• Qualifications: A PhD (or equivalent research experience) is ideal but not required. Strong candidates may also have a Bachelors or Masters degree and 3 years of relevant research computing experience whether in academia national labs or industry R&D demonstrating the required skills.

Desired requirements

• Scientific domain experience: Background in computational analysis of research data; domain expertise relevant to pharma R&D (e.g. deep learning medical imaging molecular dynamics or omics). Contributions to publications preprints or open-source research software are a plus.
• Workflow engines: Experience with Nextflow or Snakemake in research pipelines and an understanding of FAIR/reproducible research practices.
• Software engineering: Dedication to guidelines including documentation version control testing containerisation and packaging for reproducible research.
• DevOps & cloud: Familiarity with DevOps cloud deployment and infrastructure-as-code/automation in the context of scientific workloads.
• Education delivery: Experience designing and delivering technical training workshops or course materials for researchers or students.

Why AstraZeneca

Join a mission that shapes the future of scientific research and improves patient outcomes. At AstraZeneca youll work where science meets technology accelerating discovery and turning data into impact for patients worldwide. If you thrive at the intersection of academic research and robust engineering this is a place to magnify your impact.

Ready to make a difference Please submit your CV and a cover letter explaining your motivation for applying and highlighting your academic research experience (e.g. lab collaborations publications teaching or mentoring and research software contributions) by 13th of April 2026.

Date Posted

Closing Date