Senior Scientist, Cell Therapy Bioscience

AstraZeneca•Gaithersburg, MD

1d•Onsite

About The Position

This is a predominantly laboratory-based discovery position focused on immunology, cellular engineering, and functional characterization of engineered immune cells. The Senior Scientist will apply quantitative and computational skills to guide experimental design, interpret complex datasets, and advance next-generation cell therapies. The role involves hands-on research alongside use of statistical, visualization, computational biology, and AI/ML-enabled approaches to support scientific decision-making. Working within multidisciplinary project teams, the scientist will contribute to scientific strategy, project planning, and decisions while remaining directly engaged in laboratory research. The position requires independent experimental work, clear interpretation and communication of results, and effective collaboration with computational and data science colleagues. The scientist will also maintain awareness of developments in cell therapy, immunology, cellular engineering, gene editing, and AI-enabled drug discovery.

Requirements

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.
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-cell, T-cell, and immune-cell biology.
Extensive hands-on experience designing and executing immune-cell functional assays, including 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.
Ability to independently design experiments, troubleshoot technically challenging studies, critically interpret results, and translate findings into 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 collaborate effectively with computational biology, bioinformatics, and data science partners.
Understanding of potential applications and limitations of AI and machine-learning approaches in biological research, and ability to interpret and apply outputs in an experimental context.
Ability to work independently, manage multiple priorities, and plan laboratory activities against project objectives.

Nice To Haves

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 support biological interpretation, hypothesis generation, or experimental planning.
Experience with in vivo studies, including experimental design, interpretation, and integration of in vitro and in vivo findings.
Strong scientific track record demonstrated through publications, patents, scientific presentations, and/or contributions to drug discovery pipeline programs.
Previous experience in a pharmaceutical or biotechnology research environment.

Responsibilities

Conduct hands-on drug discovery research experiments independently.
Design and execute functional studies assessing 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 reach conclusions and define next experiments.
Assess and report data in the context of drug discovery, formulate conclusions independently, and determine future experiments.
Apply appropriate 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, generate hypotheses, and inform experimental prioritization.
Contribute to scientific strategy and project planning, prioritizing experimental workstreams to address biological questions and deliver high-quality data against project objectives and timelines.
Collaborate within multidisciplinary project teams and communicate experimental findings, interpretations, and recommendations through presentations, reports, and project discussions.
Share relevant external published papers with peers.
Prepare and deliver presentations within the Cell Therapy Unit and across other functions.
Ensure own work and peers’ work comply with relevant internal AstraZeneca standards and external regulations.
Maintain awareness of developments in Cell Therapy, immunology, cellular engineering, gene editing, and AI-enabled drug discovery, and assess their potential relevance to laboratory programs.