Senior Scientist, AI for Translational Sciences

AstraZeneca; Barcelona; Híbrido; EUR 70.000 - 90.000; Jornada completa

Descripción de la vacante

AstraZeneca plc in Barcelona combines AI for Translational Sciences with hands-on molecular data analysis. Join a growing team of ML/AI bioinformaticians to advance translational science using DNA sequencing, single-cell and bulk transcriptomics, proteomics, and digital pathology.

Seeking candidates with 4+ years of ML/AI experience in omics data, strong Python skills, and proficiency in PyTorch. You will design innovative AI analyses and contribute to data-driven decision making in a

Formación

• Master’s degree or Ph.D. with 4+ years in ML/AI molecular data analysis
• Expertise in AI/ML modelling for molecular data
• Strong stats, cross-study validation, data leakage prevention, and generalisability checks
• Proficient in Python; experience with PyTorch and related tools

Responsabilidades

• Design and apply computational and AI analysis methods for molecular data
• Develop AI modelling solutions and agentic systems for data-driven decisions
• Collaborate with researchers across teams to advance translational science
• Maintain high-quality standards with robust testing and reproducibility

Conocimientos

Molecular omics data analysis

AI/ML modelling

Statistics & model evaluation

Python

Git

Unix/Linux

AWS

Collaboration & communication

Educación

Master’s degree in Bioinformatics/Computational Biology/ML or related

Ph.D. in Bioinformatics/Computational Biology/ML or related

Herramientas

PyTorch

Transformers

huggingface_hub

Conda

Descripción del empleo

Role Based in Barcelona : 3 days onsite/2 days work from home.

Accountabilities:

Join our growing AI for Translational Sciences team to support AstraZeneca strategic initiatives in machine learning and bioinformatics analysis of molecular data, including DNA sequencing, single-cell and bulk transcriptomics, proteomics, spatial, and digital pathology. As an ML/AI bioinformatician with expertise in NGS omics data, you'll design and apply innovative computational & AI analysis methods to advance our research portfolio. Working within a team and maintaining the highest quality standards, your strong quantitative skills will help build AI modelling solutions and agentic systems to interrogate diverse molecular datasets, empowering researchers to use AI systems for data-driven decision-making, translational science, and biomedical knowledge generation.

Essential Skills/Experience:

• Master’s degree in Bioinformatics, Computational Biology, Machine Learning, or a related field with 4+ years of applied experience in ML/AI molecular data analysis; or Ph.D. in Bioinformatics, Computational Biology, Machine Learning, or a related field
• Expertise in AI/ML modelling approaches to molecular (omics, imaging) data
• Strong statistical and model-evaluation skills, including appropriate baseline selection, patient-level and cross-study validation, prevention of data leakage, handling of confounding and batch effects, and assessment of uncertainty and generalisability
• Hands-on experience implementing and adapting deep-learning models using frameworks such as PyTorch, transformers, huggingface_hub
• Deep understanding of at least one type of molecular profiling data (e.g. RNA or DNA sequencing) and experience in analysing human Illumina NGS data
• Understanding of drug discovery biology: target identification, target validation, mechanism of action, or translational science
• Experience using AI tools/agentic frameworks like coding copilots and research assistants
• Proven programming skills (Python essential) and familiarity with software development best-practices (end-to-end tests, unit testing, version control with git)
• Experience working in Unix/Linux environments, familiarity with package management (e.g. Conda)
• Cloud computing (preferably AWS) or High-Performance Computing (HPC)
• ‘Builder’ mindset, strategic thinker, and experience leading projects
• Strong, professional communication skills and excellent attention to detail, capable of developing effective collaborative relationships with diverse teams of technical and non-technical analysts, engineers, scientists, strategists
• Experience working within a team environment

Desirable Skills/Experience:

• Experience working with patient data from clinical trials and biomarker development
• Experience with biological foundation models such as BulkFormer, scGPT and DNABERT
• Understanding of modern deep learning architectures such as Transformers, CNN and GRU
• Experience with exploring explainability of deep learning models on multi-omics data
• Well networked within external bioinformatics, NGS, and AI/ML communities
• Experience working in pharma or biotech R&D

At AstraZeneca, we are committed to creating the future of medicine by becoming a healthcare provider beyond medicines. We focus on being truly patient-centric by using technologies to better understand diseases, develop new medicines, and support patients comprehensively. Our digitally-enabled Research & Development cycle enhances clinical trials, data collection, digital therapeutics for rapid diagnostics, wearables, machine learning, visual analytics for informed decision-making, integrated data for improved patient outcomes, and insights for the next generation of products. Here, you are empowered to explore and disrupt while working on cutting-edge innovations. If you thrive on adapting your skills and learning from setbacks as we evolve and innovate simultaneously, AstraZeneca is the place for you.

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 is. 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 authorization and employment eligibility verification requirements.