Senior Scientist, Cell Therapy Full-time NEW

Senior Scientist, Cell Therapy

We are seeking a highly motivated Senior Scientist, Cell Therapy to join our discovery research team. This is a predominantly laboratory-based role requiring strong hands-on expertise in immunology, cellular engineering, and the functional characterization of engineered immune cells.

The successful candidate will combine experimental excellence with a strong quantitative and data-driven mindset. You will design and execute rigorous laboratory studies, analyze complex experimental datasets, and integrate findings across functional, phenotypic, and other relevant datasets to advance next-generation cell therapies.

The role also provides an opportunity to apply computational, data science, and AI/ML-enabled approaches to experimental research. The successful candidate will use appropriate statistical and visualization methods and collaborate closely with computational biology, bioinformatics, and data science colleagues. Familiarity with AI and machine-learning concepts will enable the scientist to ask the right biological questions, interpret computational outputs, and identify opportunities to improve experimental design and scientific decision-making.

Working within multidisciplinary project teams, the Senior Scientist will contribute to scientific strategy, project planning, and decision-making while remaining directly engaged in laboratory research.

Key Responsibilities

• Independently design, execute, analyze, and interpret hands-on drug discovery experiments supporting Cell Therapy programs.
• Design and perform functional studies to characterize immune-cell activation, cytotoxicity, proliferation, cytokine production, phenotype, fitness, and other relevant biological 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 design, acquisition, analysis, and biological interpretation.
• Integrate findings across functional assays, flow cytometry, and, where relevant, omics and in vivo datasets to generate clear conclusions and define subsequent experiments.
• Analyze and interpret experimental data within the broader context of drug discovery, independently formulate conclusions, and recommend next steps.
• Apply fit-for-purpose statistical analysis, data visualization, and reproducible data-handling practices to experimental datasets.
• Use established computational tools and AI/ML-enabled approaches, 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 and matrixed project teams, including close partnership with computational biology, bioinformatics, data science, translational, and other research colleagues.
• Communicate experimental findings, scientific interpretations, and recommendations clearly through presentations, reports, and project discussions within the Cell Therapy Unit and across functions.
• Maintain awareness of emerging advances in Cell Therapy, immunology, cellular engineering, gene editing, and AI-enabled drug discovery, and evaluate their potential relevance to research programs.
• Ensure that laboratory activities and scientific practices comply with relevant internal standards and applicable external regulations.

Essential Requirements

• PhD in Immunology, Cell Biology, Molecular Biology, Bioengineering, or a related discipline, with demonstrated application to immunology and/or Cell Therapy, and at least 1 year of industry experience.
• Demonstrated experience conducting independent research in Cell Therapy, Immunology, Immuno-Oncology, or a closely related field.
• Strong understanding of T-cell and immune-cell biology.
• Extensive hands-on laboratory experience designing and executing immune-cell functional assays, including activation, cytotoxicity, proliferation, cytokine production, and/or other relevant functional readouts.
• Demonstrated experience with primary human immune-cell culture and genetic manipulation, transfection, and/or viral transduction.
• Strong expertise in multiparameter flow cytometry, including experimental design, acquisition, analysis, and biological interpretation of complex datasets.
• Demonstrated ability to independently design experiments, troubleshoot technically challenging studies, critically evaluate results, and translate findings into clear conclusions and next steps.
• Strong quantitative and data-driven mindset, including experience applying appropriate statistical approaches and integrating findings across multiple experiments.
• Ability to work with complex biological datasets and collaborate effectively with computational biology, bioinformatics, and data science colleagues.
• 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 and timelines.
• Strong written and verbal scientific communication skills and the ability to work effectively in a multidisciplinary, collaborative environment.

Desired Experience

• Experience with advanced CAR-T or other engineered immune-cell approaches.
• Experience with cellular engineering and/or gene-editing technologies.
• Experience analyzing high-dimensional biological datasets, including complex flow cytometry, single-cell or bulk transcriptomics, spatial data, and/or proteomics.
• Practical familiarity with Python and/or R for data analysis and visualization, or sufficient familiarity to work effectively 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 programs.
• Previous experience in a pharmaceutical or biotechnology research environment is preferred.