Senior Scientist, Cell Therapy Bioscience

Senior Scientist, Cell Therapy Bioscience
Laboratory-based discovery with data-driven and AI/ML-enabled analysis
About AstraZeneca
At AstraZeneca, we are driven by our ambition to transform science into life-changing medicines for patients. We bring together deep biological insight, innovative technologies and data-driven approaches to tackle complex scientific challenges and accelerate the discovery and development of new therapies. We foster a collaborative and inclusive environment where diverse perspectives, scientific rigor and bold thinking help us push the boundaries of what is possible.
Within Cell Therapy, we are advancing the next generation of engineered cell therapies by integrating cellular and molecular biology, immunology, bioengineering, computational approaches and data science. Our scientists work at the interface of experimental science and emerging technologies, bringing curiosity, collaboration and a data-driven mindset to the discovery of innovative cell therapies.
About the Gaithersburg Site
Our Gaithersburg, Maryland campus is a major U.S. hub for R&D and Oncology, bringing together multidisciplinary scientists, modern laboratories and cross-functional teams to advance innovative medicines from discovery through development. The collaborative environment enables scientists with diverse expertise to work together, leverage cutting-edge technologies and translate scientific discoveries into meaningful advances for patients.
Position Summary
This is a predominantly laboratory-based discovery position requiring strong hands-on expertise in immunology, cellular engineering and the functional characterization of engineered immune cells. The ideal candidate will complement this laboratory expertise with quantitative and computational skills. They will apply these capabilities to guide experimental design, interpret complex datasets and advance next-generation cell therapies.
The role requires a strong quantitative and data-driven mindset. The scientist will analyze complex experimental datasets, use appropriate statistical and visualization approaches, and partner effectively with computational and data science colleagues. Familiarity with computational biology, AI and machine-learning concepts is important for asking the right questions, interpreting outputs and identifying opportunities to improve experimental design and scientific decision-making.
Working within multidisciplinary project teams, the scientist will contribute to scientific strategy, project planning and decision-making while remaining directly engaged in laboratory research.
Key Responsibilities
Conducts hands-on drug discovery research experiments independently
Design and execute functional studies to assess immune-cell activation, cytotoxicity, proliferation, cytokine production, phenotype, fitness and other relevant functional properties.
Perform primary human immune-cell culture, genetic manipulation, transfection and/or viral transduction, and optimize experimental methods as needed.
Design and execute multiparameter flow cytometry studies, including panel planning, acquisition, analysis and biological interpretation.
Integrate findings across functional assays, flow cytometry and, where relevant, omics or in vivo datasets to generate clear conclusions and define next experiments.
Assesses and reports data with a clear understanding of its implications within the overall context of drug discovery, independently formulate conclusions, and determine future experiments
Works collaboratively in a matrix environment
Shares relevant external published papers with peers
Prepares and delivers presentations within the Cell Therapy Unit and across other functions
Ensures own work, and work of peers, are compliant with relevant internal AstraZeneca standards and external regulations
Apply fit-for-purpose statistical analysis, data visualization and reproducible data-handling practices to experimental datasets.
Use existing computational tools and AI/ML-enabled outputs, in partnership with specialists where appropriate, to explore biological patterns, support hypothesis generation and inform experimental prioritization.
Contribute to scientific strategy and project planning, prioritizing experimental workstreams to address key biological questions and deliver high-quality data against project objectives and timelines.
Collaborate effectively within multidisciplinary project teams and communicate experimental findings, scientific interpretations and recommendations through presentations, reports and project discussions.
Maintain awareness of emerging developments in Cell Therapy, immunology, cellular engineering, gene editing and AI-enabled drug discovery, and assess their potential relevance to laboratory programs.
Essential Requirements (education, experience and skills)
• PhD with relevant research experience in Immunology, Cell Biology, Molecular Biology, Bioengineering or a related discipline, with demonstrated application to immunology and/or Cell Therapy. Minimum of 0-3 years of relevant experience.
• Demonstrated experience conducting independent research in Cell Therapy, Immunology, Immuno-Oncology or a closely related field.
• Strong understanding of NK and T-cell and immune-cell biology.
• Extensive hands-on laboratory experience designing and executing immune-cell functional assays, including cell activation, cytotoxicity, proliferation, cytokine and/or other relevant functional readouts.
• Demonstrated experience with primary human immune-cell culture, genetic manipulation, transfection and/or viral transduction.
• Strong expertise in multiparameter flow cytometry, including experimental design, acquisition, analysis and interpretation of complex datasets.
• Demonstrated ability to independently design experiments, troubleshoot technically challenging studies, critically interpret results and translate findings into clear conclusions and next steps.
• Strong quantitative and data-driven mindset, including experience applying appropriate statistical methods and integrating findings across experiments.
• Ability to work with complex biological datasets and to collaborate effectively with computational biology, bioinformatics and data science partners.
• Clear understanding of the potential applications and limitations of AI and machine-learning approaches in biological research, with the ability to interpret and apply outputs in an experimental context.
• Ability to work independently, manage multiple priorities and effectively plan laboratory activities against project objectives.
Desired Qualifications
• Experience with advanced CAR-T engineering.
• Experience analyzing high-dimensional biological data, such as complex flow cytometry, single-cell or bulk transcriptomics, spatial data and/or proteomics.
• Practical familiarity with Python and/or R for data analysis, visualization or communication with computational collaborators.
• Experience using established bioinformatics, data-science or AI/ML tools to supp